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About NewsBreak Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech. Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale. Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence. If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about AI Engineer — AI-Native Product Engineering Location: Mountain View, CA About the Team We are rethinking how software is built in an AI-native world. AI is becoming the default way we design, build, test, debug, and operate software. Engineers on this team work with coding agents to ship production products quickly, while setting the architecture, context, quality standards, and guardrails that make AI-generated software reliable. This role is frontend-leaning, but not frontend-limited . We are moving away from traditional frontend/backend boundaries. You will start from strong client-side product engineering skills and use AI to work effectively across APIs, backend services, data flows, and developer tooling. The expectation is simple: own the problem end to end, not just one layer of the stack. What You’ll Do Build user-facing products end to end. Own features from product requirements and frontend architecture through API integration, backend changes, testing, rollout, and production metrics. Use AI as a core development tool. Work with coding agents to generate, refactor, test, debug, and understand code, while providing the context and validation needed for production quality. Own frontend architecture and product quality. Build maintainable component systems, state and data flows, performance-sensitive experiences, and reliable testing patterns for consumer-scale products. Cross frontend/backend boundaries. Make the API or backend changes needed to complete a product experience rather than handing work off at team boundaries. Set a high bar for AI-generated code. Review outputs critically and use automated tests, observability, staged rollout, and rollback mechanisms to verify correctness. Improve the AI-native engineering workflow. Turn repetitive development work into reusable agent workflows, tooling, conventions, and playbooks that make the team faster. Modernize existing systems. Refactor legacy frontend and service code incrementally so both engineers and AI agents can understand and modify it safely. Own production outcomes. Investigate performance issues, regressions, and incidents using logs, metrics, experiments, and AI-assisted debugging. What We’re Looking For 3+ years of software engineering experience , with strong depth in frontend or client-side product engineering. Strong JavaScript/TypeScript fundamentals and hands-on experience with React or a comparable modern frontend framework. Experience shipping meaningful user-facing features in production and making frontend architecture decisions around components, state, data flow, performance, or testing. Evidence that you can work beyond the frontend layer — for example, designing or modifying APIs, backend services, data contracts, or developer tooling. Hands-on use of modern AI coding tools or coding agents as part of real development work, not only occasional autocomplete. Strong engineering fundamentals and the ability to reason about system behavior, debugging, reliability, testing, and performance. Ability to learn unfamiliar technologies quickly and use AI effectively to expand into adjacent parts of the stack. Strong product mindset: you care about user experience and business outcomes, not just implementation. Comfortable operating in a fast-moving environment where engineers help define the solution rather than simply execute a detailed specification. Bonus Points Experience building AI-native or agent-powered user experiences. Experience building or operating coding agents, LLM workflows, or developer productivity tools. Backend experience with Java, Kotlin, Python, Node.js, or similar technologies. Experience with recommendation, feed, search, ads, growth, or other large-scale consumer products. Experience improving web performance, experimentation infrastructure, design systems, or CI/CD quality gates. Experience shipping 0→1 products in a small, highly autonomous team. The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $118,000 — $212,000 USD CPRA Privacy Notice for California Candidates

About NewsBreak Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech. Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale. Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence. If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about About the team The User Signal team sits at the heart of our in-house advertising platform. We collect, process, and activate user signals — behavioral events, contextual data, engagement history, and identity signals — and turn them into the features and audiences that power ads targeting, bidding, and ranking across the company's ad stack. The quality of our signals directly determines how well every downstream ML model performs: better signals mean better targeting, higher CTR/CVR, and stronger monetization. We own the full lifecycle — from raw event ingestion and large-scale feature pipelines, to identity-prediction models, embeddings, and online serving — and we close the loop by applying those outputs inside the ads models that consume them in real time. About the role We are looking for an experienced Senior Machine Learning Engineer to design and build the data and ML systems that transform raw user signals into production targeting and bidding features. This is a hands-on, high-ownership role that blends ML modeling , large-scale data engineering , and production ML systems . You will own significant pieces of the signal-to-model pipeline end to end: defining and building features at scale, developing models for user understanding — most importantly identity prediction — and then applying those predictions directly inside the ads targeting, bidding, and ranking models to drive measurable lift. You won't just hand features off to a downstream team; you'll close the loop, ensuring everything is served online with the freshness, latency, and reliability that real-time bidding demands. You'll partner closely with Ads, Data, and Infra teams, and you'll be expected to drive technical direction — not just execute well-scoped tasks. Responsibilities Build user-signal features at scale : design, implement, and own offline and online feature pipelines (batch + streaming) that turn raw user events into high-quality targeting and bidding features. Develop user-understanding models — especially identity prediction : build and improve models such as identity prediction, user/content embeddings, intent and conversion prediction, and signal-quality / value models that feed ads targeting and bidding. Apply model outputs inside ads models : integrate identity-prediction results and other user signals directly into the ads targeting, bidding, and ranking models — owning the impact all the way to revenue, not just the upstream features. Own the model lifecycle : data preparation, feature engineering, training, offline/online evaluation, deployment, monitoring, and iteration — with rigorous A/B testing and clear business metrics (CTR, CVR, ROAS, revenue). Bridge modeling and serving : ensure features and model outputs are available online with the freshness and low latency required by high-QPS real-time bidding, working across feature stores, embedding stores, and serving infra. Improve signal quality and coverage : identify gaps, biases, and freshness issues in user signals; build the data quality, labeling, and validation systems that keep features trustworthy. Collaborate cross-functionally with Ads ranking/bidding, Data, and Platform teams to align signal and feature design with downstream model and business needs. Provide technical leadership : drive design reviews, set best practices for ML and feature engineering, mentor engineers, and raise the quality bar for the team. Requirements Bachelor's or Master's degree in Computer Science, Machine Learning, Statistics, or a related quantitative field (or equivalent practical experience). 5+ years of industry experience as an ML engineer / applied scientist, building and shipping ML models in production (not just research or offline prototyping). Strong foundation in machine learning: feature engineering, supervised learning, embeddings/representation learning, and offline + online evaluation methodology. Proficiency in Python and a solid ML stack (e.g. PyTorch or TensorFlow , scikit-learn, pandas/NumPy). Hands-on experience with large-scale data processing for ML — e.g. Spark , Flink, SQL/Presto/Trino — including building production feature or training-data pipelines. Experience taking models from idea to production: training, deployment, monitoring, and iterating based on real metrics and A/B tests. Strong analytical and problem-solving skills, and the ability to reason about model behavior, data quality, and business impact end to end. Preferred Qualifications Direct experience in Ads, recommendation, search, or growth ML — especially targeting, bidding, ranking, CTR/CVR prediction, or identity prediction . Experience with user-signal / behavioral data : event pipelines, identity prediction, user embeddings, and applying model outputs back into downstream ranking/bidding models. Familiarity with online feature serving — feature stores, embedding/vector stores, and low-latency, high-QPS inference for real-time bidding. Experience with streaming systems (Kafka, Flink, Spark Streaming) for real-time feature computation. Knowledge of the big-data ecosystem (Hadoop, Spark, Hive, Presto/Trino) and modern ML platforms / MLOps tooling (training orchestration, experiment tracking, model registries, feature stores). Experience with large-scale / distributed model training and inference optimization (e.g. distributed training, embedding tables, quantization, efficient serving). A track record of measurable business impact (revenue, ROAS, CTR/CVR lift) from ML work, and of driving technical direction across teams. What we offer The chance to own a mission-critical part of the ads stack — the user signals and features that every targeting and bidding model depends on. Real end-to-end ownership: from raw signal to production model to measurable revenue impact, with high visibility across Ads and business leadership. Collaboration with strong Ads, ML, and Data engineers on internet-scale problems. Competitive compensation and benefits. Benefits We offer a competitive benefits package: Health, dental, and vision care for you and your family (100% coverage for employee) Top-tier 401(K) plan with company matching Paid time off and paid holidays FSA, HSA and commuter benefits programs Team activity budget The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $185,000 — $235,000 USD CPRA Privacy Notice for California Candidates

About NewsBreak Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech. Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale. Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence. If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about About Nearby AI Nearby AI is a new company from NewsBreak building a trust-first marketplace for local home services. We help homeowners understand a problem, what it should reasonably cost, and whether to hire at all before they are connected to a provider, and we help service providers win work on fit and outcomes rather than on speed of contact. Our mission: give people clarity and control from the first sign of a problem to a job done right, and give good contractors work they are equipped to win. We are a small founding team. We work from evidence, keep a written record of decisions, and hold a short set of product principles we do not trade for revenue: no pay-for-rank, no sharing of customer contact information beyond what the customer approved, and no quality claims we cannot substantiate. The problem you will own In a two-sided marketplace, nearly every commitment made to a customer or a provider is delivered as a message: confirmations, time-sensitive notifications to professionals, outcome follow-ups that feed our quality measurement, shared summaries for family members, and longer-horizon engagement. Because consumer messaging in our category is regulated, the platform that sends these messages is also the system that enforces consent, preferences, and suppression. You will design, build, and own that platform across email, SMS, push, and in-app channels. Responsibilities Design and build the messaging platform: triggering, routing, templating, retries, deduplication, rate limiting, scheduling, and delivery tracking, with reliability and observability as first-class requirements. Build the consent and preference layer: per-channel consent records with provenance, opt-out and do-not-contact propagation to partners within contracted timelines, quiet hours, and suppression rules that no campaign can override. Own deliverability end to end: sender registration and reputation, authentication standards, bounce and complaint handling. Partner with data and machine-learning engineers on event-triggered engagement, including frequency management and holdout design. Provide experimentation hooks so growth can test timing, content, and channel without changes to the core platform. Establish engineering standards for a system that carries regulatory obligations, including audit trails and access controls. Qualifications Required 5+ years of backend software engineering, including ownership of a messaging, notification, or lifecycle platform. Operated that platform at meaningful scale, millions of messages per month, across at least two of email, SMS, and push. Designed event-driven systems with explicit idempotency, retry, and deduplication guarantees, and carried on-call responsibility for them. Shipped within a consent or privacy regime such as TCPA, CAN-SPAM, GDPR, or CCPA, where the system, not a policy document, enforced the rules. Hands-on production experience with a major messaging provider or platform (for example Twilio, SendGrid, Braze, Iterable, Customer.io, or an in-house equivalent), and clear judgment about build versus buy. Strong proficiency in at least one of Go, Java, Kotlin, Python, or TypeScript, plus SQL. Preferred Lifecycle or growth engineering on a large consumer product. Integrations with CRMs, call centers, or partner systems through webhook or real-time APIs. Deliverability troubleshooting at scale, including sender registration and domain reputation recovery. Experience building experimentation infrastructure. The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $150,000 — $280,000 USD CPRA Privacy Notice for California Candidates

About NewsBreak Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech. Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale. Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence. If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about About the role Own and scale the backend of NewsBreak's advertising platform end to end — from the advertiser-facing Ad Manager through the real-time bidding flow that monetizes our traffic — and act as a primary builder for our expansion into external demand and external supply. This is a senior, high-ownership role on a small team. You will be one of a handful of people who can take an ads initiative from problem statement through production revenue, and you are expected to raise the technical bar and the operational resilience of the systems you touch, not just add throughput to them. Responsibilities Bidding flow (traffic side): own the serving path end to end — ad request handling, candidate retrieval, auction server, bid server, and the event/attribution pipeline — under high-QPS, low-latency constraints. Auction optimization: improve yield across both our own auction and external auctions — floor pricing, timeout and latency budgets, network/exchange migrations — with results measured on realized CPM rather than on shipped features. Ad Manager (advertiser side): design, build, and operate campaign and line-item modeling, targeting, budget and pacing control, spend accounting and billing integrity, and advertiser-facing APIs and workflows. DSP build-out: implement and scale outbound bidding into external exchanges: OpenRTB integrations with SSPs/exchanges, creative delivery, audience matching, bid pricing and shading, budget/QPS protection, and post-bid reconciliation. Defend the revenue path: build real-time metrics, alerting, and discrepancy detection for the money path, and diagnose revenue movements quickly when they happen. Collaborate and de-risk: partner with product, algorithm/modeling, SRE, and ad ops; lead design reviews; document and share ownership so no critical ads subsystem depends on one person. Ad quality where it meets serving: support creative and landing-page policy enforcement, fraud/cloaking detection, and invalid-traffic signals as they intersect the serving path. Requirements Required 5+ years of backend engineering experience building and operating distributed, high-QPS, low-latency production services (Java, Go, C++, or similar). Strong system design fundamentals: service decomposition, data modeling, caching (e.g., Redis), streaming/messaging (e.g., Kafka), analytical query engines (e.g., ClickHouse, Trino, Spark), and cloud infrastructure (AWS). Demonstrated end-to-end ownership of a revenue-critical or transaction-critical system, including correctness of money — accounting, idempotency, reconciliation — and production operational responsibility. Comfort with ambiguity and full ownership on a small team: able to go from a business problem to a shipped, measured system without a spec handed down. Strong written communication and cross-functional collaboration; effective working with AI-assisted development workflows. Preferred Direct advertising-domain experience — DSP, SSP, ad exchange, or ad server — including OpenRTB, real-time auctions, header bidding, budget pacing, bid shading, and attribution/conversion measurement. Experience integrating with Google Ad Manager / Ad Exchange, Meta or Google ad SDKs, or major mobile exchanges. Experience integrating ML model serving (CTR/CVR prediction, ranking) into an auction under latency constraints. Experience with brand safety, ad fraud, or invalid-traffic detection. The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process. Annual Base Pay Range $155,000 — $260,000 USD CPRA Privacy Notice for California Candidates