Senior ML Software Engineer, Mapping

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other

Scale GP (Scale Generative AI Platform) is an enterprise-grade Generative AI platform providing APIs for knowledge retrieval, inference, evaluation, and more. We are seeking a strong Senior Full-Stack Engineer to help us build, scale, and refine our rapidly growing product. The ideal candidate is deeply grounded in software engineering best practices and experienced in developing and scaling modern web applications end-to-end. You will work across the stack—from React/TypeScript frontends to Python-based backends—while integrating with LLMs and machine learning systems. You will solve complex challenges in scalability, reliability, and product experience while owning significant product areas in a fast-paced environment. What You’ll Do Own major full-stack product areas , driving features from design through production deployment. Build modern frontend experiences using React and TypeScript, ensuring performance, usability, and responsiveness. Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components. Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences. Deliver experiments and new features quickly , maintaining high quality and tight feedback loops with customers. Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP. Adapt quickly —learning new technologies, frameworks, and tools as needed across the stack. Ideal Experience 5+ years of full-time engineering experience , post-graduation. Strong experience developing full-stack applications using React, TypeScript, and Python . Experience scaling or shipping products at high-growth startups . Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (tinkering or production experience welcome). Proficiency with SQL and modern API development. Experience with Kubernetes , containerization, and microservice architectures. Experience working with at leas

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Data Science team works closely with partners from Design, Product and Engineering across Airbnb’s product portfolio. Our work involves 0-to-1 innovation, applying sophisticated modeling techniques to critical Airbnb problems and finding new ways to leverage science for the good of the Airbnb community. Web prototypers work with Data Scientists to identify key questions during the development of these new solutions and build software prototypes that answer them. The work of DS prototyping covers everything from designing the right data visualization to focused explorations that help solve key design questions to broad explorations that help validate ideas. The Difference You Will Make: This role is focussed on partnering with the Data Science team to develop prototypes that show the potential of new data models targeting critical business and user problems. Step change advances in ML/AI have the potential to transform Airbnb, but doing that well requires not just building the right models, but also creating the right experience -- your work will be critical in enabling us to do that. Sophisticated and impactful models are often complex and hard to understand -- by building effective prototypes you can help close that gap and allow innovation to flourish. Your prototypes will enable leadership to make critical and strategic business decisions by demonstrating technical feasibility, suggesting implementation approaches, enabling user studies, and more. A Typical Day: As a web prototyper, you will create prototypes that enable differentiating and industry-leading produc

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About Data Engine Our Generative AI Data Engine powers the world’s most advanced LLMs and generative models through world-class RLHF (Reinforcement Learning with Human Feedback), human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. Our Approach As part of the interview process, you’ll be considered for opportunities across several teams within the GenAI Engineering organization, based on your interests, expertise, and business needs. Potential team placements include Allocation, Growth, Frontier Data, Trust & Safety, Pay, Operator, or Tasking Experience. Together, these teams power Scale’s AI data operations - from building high-impact datasets that push the boundaries of LLM capabilities, to optimizing contributor onboarding and incentives, to safeguarding data integrity through advanced trust, safety, and security measures. They work at the intersection of ML, operations, and analytics to ensure we deliver the highest-quality data at scale. Responsibilities: Design, build, and maintain robust, scalable systems across the full stack, including front-end, back-end, and infrastructure layers Implement high-impact features using modern technologies such as TypeScript, React, Node.js, MongoDB, Elasticsearch, and Temporal Collaborate closely with internal operators (your use

About the Team At DoorDash, we’re reimagining how people connect with the things they need — whether it’s a meal, a grocery run, and anything in between. Our audiences — Consumers, Dashers, and Merchants — are at the heart of everything the Design org builds. Our content design team plays a big part in this, with each content designer shaping the experience and bringing our vision to life through clear, thoughtful language that makes our three-sided marketplace easier, faster, and more human. About the Role We’re looking for a full stack UX Design Engineer to be the technical backbone of our global Content Design org and leader who builds the platforms, tooling, and ML systems that make world-class, localized product content effortless across DoorDash, Wolt, and Deliveroo. You’ll work at the intersection of design and engineering to build content tooling and embed LLM-driven workflows into product experiences. You’ll accelerate content design AI tooling so that CD’s can focus on the highest leverage strategic work, while your tools enable product designers and cross functional partners to ship high-quality content faster across DoorDash, Wolt, and Deliveroo. You're excited about this opportunity because... Design and build internal content tools that: Help PMs and designers generate, manage, localize, and deploy product content at scale. Plug custom GPTs and other LLMs into everyday product workflows for content iteration and improvements. Own full-stack development of these tools: Build and maintain frontend experiences using React and modern JavaScript/TypeScript. Design and implement backend services and APIs (e.g., Kotlin/Java) to support content tooling, experimentation, and automation. Integrate tooling with experimentation and infra: Embed content tools into A/B testing platforms so teams can test and ship variants with minimal engineering dependency. Build pipelines from variant generation → experiment → automated deployment of winners. Operationalize