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We are looking for a Senior ML Engineer to lead foundational research in agentic AI and intelligent systems . This is a research-intensive role focused on advancing the underlying models, learning paradigms, and capabilities that enable AI agents to reason, plan, learn, remember, interact with tools, and operate effectively over complex, long-horizon tasks. This is not a prompt-engineering or agent orchestration role . We are looking for a scientist with strong fundamentals in machine learning and deep learning who can develop novel modeling and learning approaches , rather than primarily assembling existing LLMs, prompts, or agent frameworks. The ideal candidate will have deep expertise in one or more areas of generative modeling, large language models, NLP, computer vision, multimodal learning, representation learning, reinforcement learning, or related areas , along with the ability to connect these foundations to emerging agentic systems. The role will involve identifying fundamental research problems in agentic intelligence, developing new algorithms and model architectures, designing rigorous experiments, and translating research advances into product. Key Responsibilities Conduct fundamental and applied research in agentic AI, foundation models, reasoning, planning, memory, tool use, multimodal intelligence, and long-horizon interaction. Develop novel model architectures, learning algorithms, training methodologies, and inference techniques to improve the capabilities of AI agents. Advance the underlying intelligence of agents through research in LLMs, generative models, NLP, computer vision, multimodal learning, representation learning, and reinforcement learning . Investigate problems such as reasoning, planning, memory, grounding, adaptation, self-improvement, tool use, and learning from interaction . Build and evaluate research prototypes and establish rigorous experimental methodologies to validate new ideas . Rigorous experimentation to take the final solution to product , submit IP and publish at top-tier conferences . Stay at the forefront of rapidly evolving research in foundation models and agentic AI, identifying opportunities where fundamental advances can create differentiated product capabilities. Leadership & Collaboration Lead technical design reviews, write engineering RFCs, and set quality standards for the team. Mentor junior and mid-level ML engineers through code reviews, 1:1s, and pair-programming sessions. Collaborate with product, research, and infrastructure teams to translate research ideas into shipped features. Required Qualifications 9 + years of hands-on ML engineering experience in industry or research. MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field , with significant industry or research experience. Strong fundamentals in machine learning, deep learning, optimization, and statistical modeling . Demonstrated research experience in one or more of: Large Language Models and NLP Generative modeling (diffusion, flow matching, autoregressive models, VAEs, etc.) Computer Vision Multimodal foundation models Representation learning Reinforcement learning / learning from interaction Reasoning and planning Demonstrated ability to formulate novel research problems, develop new approaches , and experimentally validate hypotheses . Strong publication record and/or demonstrated track record of delivering novel ML research with measurable impact . Strong programming and experimentation skills, particularly with modern deep learning frameworks Excellent written and verbal communication skills with cross-functional stakeholders. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

We are looking for a Senior ML Engineer to lead foundational research in agentic AI and intelligent systems . This is a research-intensive role focused on advancing the underlying models, learning paradigms, and capabilities that enable AI agents to reason, plan, learn, remember, interact with tools, and operate effectively over complex, long-horizon tasks. This is not a prompt-engineering or agent orchestration role . We are looking for a scientist with strong fundamentals in machine learning and deep learning who can develop novel modeling and learning approaches , rather than primarily assembling existing LLMs, prompts, or agent frameworks. The ideal candidate will have deep expertise in one or more areas of generative modeling, large language models, NLP, computer vision, multimodal learning, representation learning, reinforcement learning, or related areas , along with the ability to connect these foundations to emerging agentic systems. The role will involve identifying fundamental research problems in agentic intelligence, developing new algorithms and model architectures, designing rigorous experiments, and translating research advances into product. Key Responsibilities Conduct fundamental and applied research in agentic AI, foundation models, reasoning, planning, memory, tool use, multimodal intelligence, and long-horizon interaction. Develop novel model architectures, learning algorithms, training methodologies, and inference techniques to improve the capabilities of AI agents. Advance the underlying intelligence of agents through research in LLMs, generative models, NLP, computer vision, multimodal learning, representation learning, and reinforcement learning . Investigate problems such as reasoning, planning, memory, grounding, adaptation, self-improvement, tool use, and learning from interaction . Build and evaluate research prototypes and establish rigorous experimental methodologies to validate new ideas . Rigorous experimentation to take the final solution to product , submit IP and publish at top-tier conferences . Stay at the forefront of rapidly evolving research in foundation models and agentic AI, identifying opportunities where fundamental advances can create differentiated product capabilities. Leadership & Collaboration Lead technical design reviews, write engineering RFCs, and set quality standards for the team. Mentor junior and mid-level ML engineers through code reviews, 1:1s, and pair-programming sessions. Collaborate with product, research, and infrastructure teams to translate research ideas into shipped features. Required Qualifications 9 + years of hands-on ML engineering experience in industry or research. MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field , with significant industry or research experience. Strong fundamentals in machine learning, deep learning, optimization, and statistical modeling . Demonstrated research experience in one or more of: Large Language Models and NLP Generative modeling (diffusion, flow matching, autoregressive models, VAEs, etc.) Computer Vision Multimodal foundation models Representation learning Reinforcement learning / learning from interaction Reasoning and planning Demonstrated ability to formulate novel research problems, develop new approaches , and experimentally validate hypotheses . Strong publication record and/or demonstrated track record of delivering novel ML research with measurable impact . Strong programming and experimentation skills, particularly with modern deep learning frameworks Excellent written and verbal communication skills with cross-functional stakeholders. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI. Stay current with advances in ML/AI and bring relevant innovations into Adobe's products. Minimum Qualifications Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field. 5+ years of professional experience building and deploying ML solutions at scale. Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks. Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring. Strong grasp of model optimization, inference efficiency, and production system integration. Preferred Qualifications Experience in fraud detection, anomaly detection, or behavioral modeling. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI. Stay current with advances in ML/AI and bring relevant innovations into Adobe's products. Minimum Qualifications Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field. 5+ years of professional experience building and deploying ML solutions at scale. Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks. Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring. Strong grasp of model optimization, inference efficiency, and production system integration. Preferred Qualifications Experience in fraud detection, anomaly detection, or behavioral modeling. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI. Stay current with advances in ML/AI and bring relevant innovations into Adobe's products. Minimum Qualifications Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field. 5+ years of professional experience building and deploying ML solutions at scale. Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks. Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring. Strong grasp of model optimization, inference efficiency, and production system integration. Preferred Qualifications Experience in fraud detection, anomaly detection, or behavioral modeling. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI. Stay current with advances in ML/AI and bring relevant innovations into Adobe's products. Minimum Qualifications Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field. 8+ years of professional experience building and deploying ML solutions at scale. Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks. Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring. Strong grasp of model optimization, inference efficiency, and production system integration. Preferred Qualifications Experience in fraud detection, anomaly detection, or behavioral modeling. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and production monitoring. Collaborate cross-functionally with data science, product, and platform teams; mentor junior engineers on experimentation rigor, deployment process, and responsible AI. Stay current with advances in ML/AI and bring relevant innovations into Adobe's products. Minimum Qualifications Bachelor’s degree or Master’s degree or equivalent experience in Computer Science, Machine Learning, Data Science, or related field. 8+ years of professional experience building and deploying ML solutions at scale. Strong programming expertise in Python, with hands-on experience in PyTorch, TensorFlow, or similar frameworks. Deep understanding of the end-to-end ML lifecycle—from data collection to deployment and monitoring. Strong grasp of model optimization, inference efficiency, and production system integration. Preferred Qualifications Experience in fraud detection, anomaly detection, or behavioral modeling. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com . AI Use Guidelines for Interviews: Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process. At Adobe, we empower employees to innovate with AI — and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience .