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Get to Know Our Team At Grabber Technology Solutions (GTS), we revolutionise the technology experience for every Grabber. Our mission is to empower our team with seamless and solutions that enhance their daily work. We are a diverse group of forward-thinkers committed to creating personalised IT experiences. If you're passionate about customer-centric innovation and on technology at Grab, come join us and help shape the future of technology! Get to Know the Role Reporting to the Head, End User Computing, you will lead the Business Applications Engineering team responsible for building and operating AI-enabled enterprise applications and internal platforms. As the team's people and technical leader, you will manage team health, engineering capability, delivery outcomes, technical direction and production quality. Working with Product, GTS stakeholders and partners, you will translate product priorities into reliable systems while creating an environment where engineers can deliver independently, learn quickly and improve continuously. Your success means building an empowered team that delivers measurable business value and operates reliably, while establishing and improving the team's agentic engineering harness. This role is onsite based in our Petaling Jaya, Malaysia office. The Critical Tasks You Will Perform You will lead through people, technical direction, and delivery ownership. Build and develop a engineering team by setting clear expectations, coaching team members, fostering psychological safety, and creating an inclusive culture. Set the team's engineering strategy, goals, and technical quality bar, leading architecture, design, and code reviews. Partner with Product to shape the roadmap, define success measures, run planning cycles, and create clear execution plans with ownership, milestones, risks, and dependencies. Lead delivery of AI-first applications and internal platforms from design through production, adoption, support, and continuous improvement. Establish the team's agentic engineering harness and reusable engineering foundations. Continuously improve these foundations, including development workflows, tool use, service architecture, APIs, event contracts, data access, identity, evaluation, testing, and deployment. Own reliability and responsible engineering practices across the team, including observability, availability, security, privacy, data governance, cost management, on-call readiness, incident response, and postmortems. What Essential Skills You Will Need You will bring people leadership, software engineering fundamentals, technical judgement, and delivery ownership. You will have 8+ years of software engineering experience and experience managing or leading software engineers. You will have hands-on experience designing and operating enterprise applications, APIs, integrations, and distributed systems. You will have experience owning production reliability, observability, security, incident response and continuous improvement for software systems. You will have experience planning and delivering engineering roadmaps using clear goals, milestones, metrics, risk management, and dependency management. You will have experience hiring, coaching, developing, and managing the performance of engineers while building healthy and inclusive teams. You will have experience using agentic engineering tools such as Cursor, Claude Code, or Codex, and applying emerging technologies to improve engineering productivity and product delivery. You will be able to communicate complex technical ideas and align Product, Engineering, business, and partner teams around shared outcomes. Nice to haves skills Experience building internal enterprise applications, business platforms, service management tools, or workflow automation. Experience with SaaS replacement, platform migration, vendor consolidation, or reducing technology dependency. Experience designing AI-enabled applications, agentic systems, or MCP-based integrations. Experience with platformisation, reusable services, developer productivity tooling, or engineering enablement systems. Experience leading distributed teams or managing staffing and capacity across multiple technical disciplines. Experience establishing engineering standards, reusable patterns or development practices adopted by multiple teams. Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For at Grab We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get to Know the Team At Grabber Technology Solutions (GTS), we revolutionise the technology experience for every Grabber. Our mission is to empower our team with seamless and solutions that enhance their daily work. We are a diverse group of forward-thinkers committed to creating personalised IT experiences. If you're passionate about customer-centric innovation and on technology at Grab, come join us and help shape the future of technology! Get to Know the Role Reporting to the Engineering Manager, Business Applications, the Senior Engineer will contribute to the development of AI-first enterprise applications and internal platforms. You will own features and clearly defined technical outcomes from design through production, while helping the team build secure, reliable and observable systems. You will work with the Product Manager, other engineers and business stakeholders, guide junior engineers through feedback and code reviews, and use data and user feedback to improve solutions and delivery practices. You will be reporting to Head, EUC and IT Governance. This role is onsite based in our Petaling Jaya, Malaysia office. The Critical Tasks You Will Perform: You will design, build and maintain production features, services, integrations and workflow automations for internal enterprise applications. You will manage, making sound trade-offs across quality, maintainability, security, reliability, cost and delivery speed. You will contribute to reusable foundations for agentic applications, including APIs, data access, identity, permissions, auditability, human escalation and operational guardrails. You will apply automated testing, evaluation, observability, security controls and production monitoring throughout the software delivery lifecycle. You will prototype and rapidly iterate on solutions using data, user feedback and minimum viable implementations, then harden successful approaches for production. You will review code and technical designs, provide constructive feedback, share knowledge and guide junior engineers toward stronger engineering practices. You will support production delivery and incident investigation, communicate blockers early, document learnings and drive continuous improvement. What Essential Skills You Will Need You have 4+ years of professional software engineering experience, or equivalent evidence of operating at senior individual contributor scope. You have experience using agentic engineering tools such as Cursor, Claude Code, or Codex, and applying emerging technologies to improve engineering productivity and product delivery. You understand APIs, databases, software design fundamentals, system dependencies and common trade-offs in enterprise applications. You have experience writing automated tests, improving observability, investigating production issues and applying secure software practices. You can own a scoped project or technical outcome, resolve challenges, communicate blockers and deliver agreed results. You communicate clearly with technical and non-technical stakeholders and collaborate across Product, Engineering and business teams. Nice to haves skills Experience building internal enterprise applications, business platforms, service management solutions or workflow automation. Experience with AI-enabled or agentic applications, evaluation practices, tool integrations or responsible automation. Experience mentoring junior engineers, leading technical discussions or contributing to engineering standards and reusable practices. Experience working with distributed teams or delivering software used across multiple countries or business functions. Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For At Grab We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get to Know the Team At Grabber Technology Solutions (GTS), we revolutionise the technology experience for every Grabber. Our mission is to empower our team with seamless and solutions that enhance their daily work. We are a diverse group of forward-thinkers committed to creating personalised IT experiences. If you're passionate about customer-centric innovation and on technology at Grab, come join us and help shape the future of technology! Get to Know the Role The Software Engineer will contribute to the Business Applications Engineering team's work on Grab's next generation of AI-first applications and internal platforms. You will contribute throughout the technical delivery journey, from solution design and implementation through production delivery, adoption, support and continuous improvement. It uses the team's agentic engineering harness and AI-assisted development practices to build secure, reliable, and observable systems. You will be reporting to Head of Business Integration. This role is onsite based in our Petaling Jaya, Malaysia office. The Critical Tasks You Will Perform: You will build and maintain features, services, integrations, and automations for internal enterprise applications and platforms. You will contribute to reusable foundations for agentic applications, including APIs, event contracts, data access, identity, permissions, auditability, and human escalation paths. You will apply testing, evaluation, observability, security controls, and operational guardrails throughout the development and delivery lifecycle. You will build prototypes and production code to validate new ideas, resolve technical uncertainty, and accelerate delivery. You will write readable, maintainable, and well-tested code, and participate in technical design discussions and code reviews. You will support production delivery, monitoring, incident investigation, documentation, and continuous improvement. You will identify repetitive work and propose automation or AI-enabled improvements that increase team productivity. What Essential Skills You Will Need 2+ years of professional software engineering experience. You have experience developing and testing production software using at least one modern programming language. You understand APIs, databases, software design fundamentals, and system dependencies. You have experience writing automated tests and applying software quality practices. You can investigate issues, read logs, improve monitoring, and support production systems. You can explain your technical work clearly and collaborate with technical and non-technical stakeholders. You have experience engaging with agentic engineering tools (e.g. Cursor, Claude Code, Codex) and emerging technologies to enhance productivity, improve workflows, and contribute new ideas. Really nice to haves skills Experience with workflow automation, service management, or enterprise applications. Experience building AI-enabled features or working with MCP and similar system connectors. Experience with cloud services, CI/CD, observability, or production support. Experience working on internal tools or products used by multiple teams. Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For At Grab We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get to Know the Team The Growth Data Science team is a key component of our regional growth strategy. We focus on creating and implementing innovative approaches to drive growth through performance marketing automation, machine learning models, geospatial insights, user lifecycle and funnel optimisation, behavioural forecasting, and other advanced analytics methods. Our work spans across transportation, food, fintech, logistics, and platform services. Get to Know the Role We are seeking a experienced and versatile Manager, Growth Data Science - Digital Marketing with deep expertise in paid marketing measurement, AI-driven analytics, and operations to join our growing team. In this role, you'll collaborate with marketing leaders, analytics teams, and cross-functional stakeholders to solve complex digital marketing challenges using advanced measurement science, artificial intelligence, and data-driven approaches. You'll work on end-to-end paid marketing analytics initiatives, with opportunities to design and implement sophisticated attribution models, incrementality studies, media mix modeling (MMM), causal inference methodologies, and AI-powered tools that enhance reporting, measurement, and experimentation capabilities. You will directly report to the Senior Manager, you will be based working onsite. The Critical Tasks You Will Perform Paid Marketing Measurement & Analytics Partner with marketing leaders and stakeholders to understand business objectives, marketing channels, data sources, measurement constraints, and strategic priorities. Translate marketing needs into relevant measurement science solutions, evaluating multiple methodological approaches and communicating trade-offs between attribution models, incrementality testing, and causal inference methods. Design and implement advanced attribution methodologies (multi-touch, algorithmic, and rule-based models) to accurately measure campaign contribution across paid channels and customer touchpoints. Develop and execute incrementality measurement studies to isolate true campaign impact, including A/B testing, holdout analysis, and matched market approaches for paid marketing campaigns. Build and maintain Media Mix Modeling (MMM) frameworks to quantify the impact of paid marketing spend across channels, optimize budget allocation, and forecast campaign performance. Design and conduct geo-lift studies to measure causal impact of paid marketing initiatives at regional or market levels, supporting strategic decision-making and ROI validation. Conduct rigorous A/B tests and multivariate tests to improve paid campaign performance, measure incremental lift, and increase conversion rates and customer acquisition efficiency. Collaborate with stakeholders to align on measurement methodology, success metrics, deliverables, and project roadmaps for all paid marketing analytics projects. AI & Automation for Marketing Intelligence Leverage advanced AI and machine learning tools to automate reporting workflows, generate real-time marketing insights, and accelerate decision-making across paid marketing channels. Design and build AI-powered measurement and attribution tools that enhance the speed and accuracy of campaign performance analysis, reducing manual effort and improving stakeholder accessibility to insights. Implement machine learning models and algorithms to optimize campaign targeting, budget allocation, and bid strategies, translating AI predictions into actionable marketing recommendations. Develop AI-driven experimentation frameworks that automate test design, statistical analysis, and result interpretation, enabling faster iteration and more sophisticated measurement of marketing impact. Data Engineering & Operations Develop and manage detailed project plans including milestones, risks, owners, and contingency plans for measurement science projects. Create and maintain efficient data pipelines using SQL, Spark, and cloud-based big data technologies. These pipelines ingest, process, and integrate paid marketing data from ad platforms, conversion tracking systems, and internal data sources. Collect, clean, and integrate large datasets from multiple marketing channels (paid search, social, display, video) and attribution platforms to support measurement requirements. Build analytics tools and dashboards that deliver applicable insights on campaign performance, channel effectiveness, customer acquisition costs, and marketing ROI. Perform exploratory data analysis, statistical modeling, and causal inference analysis to uncover insights and inform strategic marketing decisions. Train, validate, and tune measurement models using modern statistical and machine learning techniques, ensuring model accuracy and business applicability. Document measurement methodologies, model results, and findings in clear, team member-ready formats and support implementation of insights within marketing operations. Stakeholder Collaboration & Leadership Lead cross-functional collaboration between marketing, analytics, product, and data engineering teams to ensure measurement frameworks align with business objectives. Communicate complex measurement science concepts, AI capabilities, and statistical findings to non-technical stakeholders, translating results into applicable marketing recommendations. Mentor junior analysts and data scientists on measurement methodologies, AI-driven analytics best practices, paid marketing analytics, and causal inference techniques. W What Essential Skills You Will Need 5+ years of hands-on experience in data science and analytics, with at least 3+ years specifically focused on paid marketing measurement and operations Demonstrated expertise in attribution modeling methodologies (multi-touch, algorithmic, rule-based approaches) Proven experience designing and executing incrementality studies, A/B tests, and holdout analyses for paid marketing campaigns Strong background in Media Mix Modeling (MMM) or marketing mix optimization Experience designing and conducting geo-lift studies or other geographically-based causal inference studies Familiarity with causal Hands-on experience building and deploying machine learning models for marketing applications, including model optimization and performance tuning Proficiency in Python, SQL, and tools like Pandas, Scikit-learn, and Spark Working knowledge of cloud data platforms (e.g., AWS S3, Redshift) for managing large-scale marketing datasets Experience with marketing data sources and ad platform APIs (Google Ads, Facebook Ads, etc.) Manage data pipelines and ETL processes with a solid understanding of data engineering best practices Familiarity with statistical software or packages for causal inference (e.g., CausalML, DoWhy, EconML) Familiarity with generative AI tools and large language models (LLMs) for automating insights generation and reporting Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For At Grab We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get to Know the Team The Growth Data Science team is a key component of our regional growth strategy. We focus on creating and implementing innovative approaches to drive growth through performance marketing automation, machine learning models, geospatial insights, user lifecycle and funnel optimisation, behavioural forecasting, and other advanced analytics methods. Our work spans across transportation, food, fintech, logistics, and platform services. Get to Know the Role We are seeking a experienced and versatile Manager, Growth Data Science - Digital Marketing with deep expertise in paid marketing measurement, AI-driven analytics, and operations to join our growing team. In this role, you'll collaborate with marketing leaders, analytics teams, and cross-functional stakeholders to solve complex digital marketing challenges using advanced measurement science, artificial intelligence, and data-driven approaches. You'll work on end-to-end paid marketing analytics initiatives, with opportunities to design and implement sophisticated attribution models, incrementality studies, media mix modeling (MMM), causal inference methodologies, and AI-powered tools that enhance reporting, measurement, and experimentation capabilities. You will directly report to the Senior Manager, you will be based working onsite. The Critical Tasks You Will Perform Paid Marketing Measurement & Analytics Partner with marketing leaders and stakeholders to understand business objectives, marketing channels, data sources, measurement constraints, and strategic priorities. Translate marketing needs into relevant measurement science solutions, evaluating multiple methodological approaches and communicating trade-offs between attribution models, incrementality testing, and causal inference methods. Design and implement advanced attribution methodologies (multi-touch, algorithmic, and rule-based models) to accurately measure campaign contribution across paid channels and customer touchpoints. Develop and execute incrementality measurement studies to isolate true campaign impact, including A/B testing, holdout analysis, and matched market approaches for paid marketing campaigns. Build and maintain Media Mix Modeling (MMM) frameworks to quantify the impact of paid marketing spend across channels, optimize budget allocation, and forecast campaign performance. Design and conduct geo-lift studies to measure causal impact of paid marketing initiatives at regional or market levels, supporting strategic decision-making and ROI validation. Conduct rigorous A/B tests and multivariate tests to improve paid campaign performance, measure incremental lift, and increase conversion rates and customer acquisition efficiency. Collaborate with stakeholders to align on measurement methodology, success metrics, deliverables, and project roadmaps for all paid marketing analytics projects. AI & Automation for Marketing Intelligence Leverage advanced AI and machine learning tools to automate reporting workflows, generate real-time marketing insights, and accelerate decision-making across paid marketing channels. Design and build AI-powered measurement and attribution tools that enhance the speed and accuracy of campaign performance analysis, reducing manual effort and improving stakeholder accessibility to insights. Implement machine learning models and algorithms to optimize campaign targeting, budget allocation, and bid strategies, translating AI predictions into actionable marketing recommendations. Develop AI-driven experimentation frameworks that automate test design, statistical analysis, and result interpretation, enabling faster iteration and more sophisticated measurement of marketing impact. Data Engineering & Operations Develop and manage detailed project plans including milestones, risks, owners, and contingency plans for measurement science projects. Create and maintain efficient data pipelines using SQL, Spark, and cloud-based big data technologies. These pipelines ingest, process, and integrate paid marketing data from ad platforms, conversion tracking systems, and internal data sources. Collect, clean, and integrate large datasets from multiple marketing channels (paid search, social, display, video) and attribution platforms to support measurement requirements. Build analytics tools and dashboards that deliver applicable insights on campaign performance, channel effectiveness, customer acquisition costs, and marketing ROI. Perform exploratory data analysis, statistical modeling, and causal inference analysis to uncover insights and inform strategic marketing decisions. Train, validate, and tune measurement models using modern statistical and machine learning techniques, ensuring model accuracy and business applicability. Document measurement methodologies, model results, and findings in clear, team member-ready formats and support implementation of insights within marketing operations. Stakeholder Collaboration & Leadership Lead cross-functional collaboration between marketing, analytics, product, and data engineering teams to ensure measurement frameworks align with business objectives. Communicate complex measurement science concepts, AI capabilities, and statistical findings to non-technical stakeholders, translating results into applicable marketing recommendations. Mentor junior analysts and data scientists on measurement methodologies, AI-driven analytics best practices, paid marketing analytics, and causal inference techniques. W What Essential Skills You Will Need 5+ years of hands-on experience in data science and analytics, with at least 3+ years specifically focused on paid marketing measurement and operations Demonstrated expertise in attribution modeling methodologies (multi-touch, algorithmic, rule-based approaches) Proven experience designing and executing incrementality studies, A/B tests, and holdout analyses for paid marketing campaigns Strong background in Media Mix Modeling (MMM) or marketing mix optimization Experience designing and conducting geo-lift studies or other geographically-based causal inference studies Familiarity with causal Hands-on experience building and deploying machine learning models for marketing applications, including model optimization and performance tuning Proficiency in Python, SQL, and tools like Pandas, Scikit-learn, and Spark Working knowledge of cloud data platforms (e.g., AWS S3, Redshift) for managing large-scale marketing datasets Experience with marketing data sources and ad platform APIs (Google Ads, Facebook Ads, etc.) Manage data pipelines and ETL processes with a solid understanding of data engineering best practices Familiarity with statistical software or packages for causal inference (e.g., CausalML, DoWhy, EconML) Familiarity with generative AI tools and large language models (LLMs) for automating insights generation and reporting Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For At Grab We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get To Know The Team The Agent Experience PST owns and operates the internal platforms used by Grab's support agents to serve our entire ecosystem- across every vertical and use case. Because agents rely on these tools to resolve critical issues for users and partners, our systems are built for extremely high availability, reliability, and 100% data correctness. When a user needs help with a transaction, they rely on our platform to ensure the agent has the right tools and data at the right time. Get To Know The Role We are looking for a Senior Backend Engineer in Vietnam to contribute to our internal tooling products used for our agents to serve Passengers, Drivers, and Merchants. You will report to the Engineering Manager, who is based in Singapore, and work in an on-site mode. This role is based in Vietnam. The Critical Tasks You Will Perform Design and write with the cutting edge Go language to improve the availability, scalability, latency, and efficiency of Grab's range of services Work with engineering team to explore and create new design / architectures geared towards scale and performance Participate in code and design reviews to maintain our high development standards Engage in service capacity and demand planning, software performance analysis, tuning and optimization Collaborate with product and experience teams to define and prototype feature specifications Work closely with infrastructure team in building and scaling back-end services as well as performing root cause analysis investigations Design, build, analyze and fix large-scale systems Pro-actively debug and solve production incidents during your on-call shift Participate in interview loops to help Grab continue hiring top industry talent Provide technical guidance, mentorship and knowledge sharing to peers. What Essential Skills You Will Need A degree in Computer Science, Software Engineering , Information Technology or related fields 5+ years of experience in software engineering in a distributed systems environment Strong Computer Science fundamentals in algorithms and data structures Familiarity with running large scale web services; understanding of systems internals and networking are a plus Strong understanding of system performance and scaling Proficient in English communication You can be a good coder in any language (C++, C, Java, Scala, Rust, Haskell, OCaml, Erlang, Python, Ruby, PHP, Node.JS, C# etc.), but willing to work on Golang Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For at Grab We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get to Know the Team The Streaming Data team (a.k.a. Coban) ensures seamless and secure real-time access to continuous events or streams, serving as Grab's unified access pattern for real-time data. We build the infrastructure and platform for writing and consuming real-time data, and provide a cost-effective, managed NoOps service for product and data teams across Grab. We partner closely with sister teams in DataTech to provide integrated data platforms that unlock big data innovation every day. Some examples of the team's work are shared publicly on the Grab Engineering blog: Building a self-serve streaming platform for Kafka topics, Flink, CDC pipelines, Kafka Connect, and notebooks ( An elegant platform ). Making Flink deployments safer through platform guardrails and production deployment patterns ( Safer deployment of streaming applications ). Enabling FlinkSQL exploration and productionisation so users can move faster from streaming ideas to running pipelines ( The complete stream processing journey on FlinkSQL ). Improving Flink release confidence with shadow testing ( Enhancing Flink deployment with shadow testing ). Strengthening real-time Kafka data quality with syntactic and semantic stream contracts ( Real-time data quality monitoring ). These are examples of the platform thinking this role will continue to advance: taking complex real-time infrastructure problems and turning them into reliable, self-service capabilities for Grab teams. Get to Know the Role As a Lead Flink Platform Engineer, you will lead the design, evolution, and operation of Grab's stream processing platform, with Apache Flink as a core compute engine. You will drive medium to large projects across Data Engineering Platforms, mentor senior engineers, and be a technical go-to person for platform architecture, reliability, and production operations. The role is hands-on across Flink, Kafka, AWS cloud infrastructure, Kubernetes, observability, and SRE practices. You will work onsite at Grab Singapore office, One North, and report to the Senior Data Engineering Manager. Why This Role Matters In an agentic world, high-quality real-time signals are becoming even more critical to drive automation, decision-making, and measurable business impact. Apache Flink is a critical real-time infrastructure layer for Grab. By making stream processing easier, safer, and more self-serve, this role helps unlock more real-time signals and turn data into business value across Grab. As Grab embraces agentic engineering, we welcome builders with strong data infrastructure experience and a passion for stream processing to join us. The Critical Tasks You Will Perform Lead platform work that makes stream processing easy, reliable, efficient, and secure across Grab through self-serve capabilities built into the platform. Design and build abstractions, modules, and libraries that lower the barrier to adopting Flink and reduce operational and security toil for users. Improve automation and self-service workflows that allow a small platform team to support many production Flink pipelines at scale. Drive technical design discussions, production readiness reviews, incident learning, and long-term architecture improvements. Partner with Kafka, data lake, metrics, and data governance platform teams to make real-time data pipelines reliable across the broader Grab data ecosystem. Mentor engineers through design reviews, debugging sessions, code reviews, and operational best practices. What Essential Skills You Will Need 5+ years leading teams or projects in software engineering, data engineering, or platform engineering disciplines. Experience building and operating stream processing pipelines in production, preferably with Apache Flink or Spark Streaming. Strong hands-on engineering experience with Kafka and modern programming languages such as Scala or Java. Strong fundamentals in distributed systems, scalable data processing, reliability engineering, and production operations. Ability to lead technical design, mentor engineers, communicate trade-offs clearly, and drive projects from design to production. Excitement to learn, apply new technologies, and improve platform reliability for many internal users. The nice-to-haves: Experience with Kafka Connect, Kubernetes, Go, GitLab CI, AWS, or Terraform. Experience building reusable platform abstractions, SDKs, deployment tooling, or self-service workflows. Experience operating Apache Flink in production, including high availability, checkpointing, safe deployments, and incident response. Experience with a data warehouse or data lake ecosystem such as Spark, Parquet, Iceberg, Delta, or Hudi. Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For at Grab We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

Get to Know the Team The AI Platform (AIP) team builds and operates the core ML and AI infrastructure that powers Grab. Our stack spans model serving, ML pipelines, data serving, AI infrastructure, and Applied Research. Together, AI Platform serves hundreds of data scientists and ML engineers across Grab, and is the foundation for everything from fraud detection and search ranking to foundation model efforts, adaptive experimentation, LLM fine-tuning, and the next generation of agent-driven products. Get to Know the Role As a Principal Machine Learning Engineer on AI Platform reporting to the AIP Head of Engineering, you'll be the senior technical anchor and solution architect for the platform. Your mandate is twofold: (1) Raise the ceiling and raise the floor. You'll partner with the Head of Engineering, AI Platform and Applied Research team to shape the forward roadmap, evaluate SOTA techniques worth productionizing, and drive integrations that connect AIP's capabilities into a coherent end-to-end experience. (2) You'll ensure the teams who depend on AIP can actually succeed on it — translating user pain into platform requirements, unblocking complex adoption cases, and getting hands-on where it matters. You'll take on workstreams spanning cross-entity platform consolidation, large-scale training throughput and reliability, and faster, higher-quality model iteration for AIP's most important users. This is an individual contributor role for someone who thrives at the intersection of platform engineering, applied ML, and user empathy — and who is equally comfortable writing a design doc, debugging a training job, and pairing with other teams to land their next model on the platform. The Critical Tasks You Will Perform Solution Architecture for AIP Users: Partner directly with Data Scientists and ML engineers across the company to design end-to-end solutions on AIP. Be the senior technical escalation point for complex adoption cases. Large-Scale Training: Drive the state of large-scale training on AIP — throughput, reliability, cost, and developer experience. Advise and contribute hands-on across foundation model training, RL, simulation, and LLM fine-tuning workloads. Faster Iteration and Model Quality: Attack the end-to-end loop from idea to shipped model — data, training, evaluation, deployment, monitoring. Drive measurable reductions in iteration time and measurable gains in model quality for AIP's highest-value use cases. Platform Integration: Design and drive integrations across AIP surfaces (model serving, ML pipelines, data serving, AI infra, AI Automation tooling) so users experience a coherent platform rather than a collection of services. User Experience Translation: Convert pain points surfaced through embeddings, support channels, and direct user work into functional requirements for AIP teams; propose cross-platform solutions that raise the bar for the DS and MLE personas. Enablement at Scale: Produce reference architectures, patterns, and opinionated best-practice guidance so the next hundred ML use cases land on AIP cleanly, without requiring bespoke platform-team involvement every time. Strategic Roadmap Definition & Mentorship: Stay current with SOTA across ML infrastructure, LLM serving, training systems, and RL; partner with the AIP HoE to decide what Grab should adopt, build, or skip. Raise the technical bar across AIP through code, design reviews, written artifacts, and direct mentorship of senior engineers across the org. What Essential Skills You Will Need Advanced MLOps & ML Platform Engineering: Expert-level mastery of ML lifecycle platforms (e.g., Kubeflow, MLflow, Triton, TorchServe) and distributed training frameworks (PyTorch, Ray, Horovod). Distributed Systems & Infrastructure: At least 10 years of experience in Kubernetes, containerization, and high-performance computing clusters (GPUs/TPUs). Experience optimising large-scale data and model pipelines. Architecture Design: Outstanding system design capability for available, scalable, and secure multi-tenant platform services. AI/LLM System Experience: Hands-on experience with LLM orchestration, fine-tuning infrastructure, or serving optimization (vLLM, TensorRT-LLM). Innovation & AI Fluency: A learning mindset to evaluate and implement state-of-the-art (SOTA) infrastructure paradigms, guiding the team on what to build versus what to skip. Adaptive Execution & Ownership: You can operate independently in high-ambiguity environments, taking full end-to-end accountability for complex system integrations and platform consolidation. Coaching with Care: Commitment to raising the engineering bar. Mentor senior engineers and foster a culture of technical excellence and collaboration. Life at Grab We care about your well-being at Grab, here are some of the global benefits we offer: We have your back with Term Life Insurance and comprehensive Medical Insurance. With GrabFlex, create a benefits package that suits your needs and aspirations. Celebrate moments that matter in life with loved ones through Parental and Birthday leave , and give back to your communities through Love-all-Serve-all (LASA) volunteering leave We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges. Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours What We Stand For at Grab We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.