Senior Staff Machine Learning Scientist Jobs

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . As a Senior Staff Machine Learning Engineer, Feed Relevance , you'll drive the development of GenAI-powered recommendations, leveraging Reddit’s unique community landscape, rich conversational data, and dynamic engagement patterns. Your deep modeling expertise will directly shape the core architectures behind feed ranking, enabling breakthrough personalization for tens of millions of users. Responsibilities: Deliver on technical initiatives that have significant company-wide impact Set technical direction for the broader Relevance and Feeds teams at Reddit, able to identify opportunities and influence strategy across multiple orgs Work with management on goal setting, planning, and de-risking critical projects Mentor and grow Senior and Staff engineers Create a strong healthy engineering culture Qualifications: 10+ years of industry experience building systems for relevance driven products Subject matter expert in relevance, recommendation, and ML systems; able to solve complex problems in these domains that few others can Deep understanding of how to build sustainable software systems at a large scale engineering organization Experience in influencing organizations on technical direction/best practices Experience working with cross-functional teams such as design, product, business & data teams to deliver great experiences. Strong focus on user experience, usability, scalability, reliability and quality. You are an undying advocate for the user, and you have a deep intuition for how people & machines inte

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role Our robotics team is growing and we are looking for a Software Engineer to join our Sensor Data and Calibration team. We are searching for an engineer with robotics and machine learning expertise to develop synthetic sensor simulation models and algorithms. The ideal candidate has hands-on experience in the research, development, and implementation of machine learning methods (e.g., NeRF or Gaussian splatting) for generating synthetic sensor data (photorealistic images, realistic lidar and/or radar, etc.). About the Work Research, develop, and implement state-of-the-art synthetic sensor simulation methods Analyze and characterize the realism and utility of synthetic sensor data Answer critical questions about sensor data and autonomy performance Collaborate with stakeholders across autonomy, infrastructure, and systems teams on map needs and requirements Role is scoped as a Senior/Staff IC with the flexibility to grow into

About the Team The Consumer Engineering Team is responsible for helping consumers discover and order everything they love globally. Our work spans the entire consumer journey across homepage, search, store discovery, item exploration, checkout and post checkout. We aim to craft a hyper-personalized, delightful and frictionless experience for millions of our customers. About the Role As a Senior Staff Machine Learning Engineer on Core Cx, you will set the personalization (P13n) strategy for the entire consumer shopping journey and bring that strategy to life. You will use our robust data and machine learning infrastructure to implement new ML solutions to make the consumer search experience more relevant, seamless, and delightful across restaurant, grocery, retail and all business at DoorDash . You will modernize the recommendation system leveraging AI. You will demonstrate a strong command of production level machine learning, experience with solving end-user problems, and collaborate well with multi-disciplinary teams. You're excited about this opportunity because you will… Drive the engineering vision, strategy, and execution for an organization of 150+ Grow, build, and nurture impactful business-focused product engineering teams. Scale the team by developing leaders internally and attracting world-class talent Mentor and guide a fast-growing organization in setting the right architectural patterns, working with various vendors in the space, and making judicious investments in the right areas anticipating what the company needs a few years down the road. Partner with Business, Product, and other Engineering teams to transform DoorDash from local commerce to agentic commerce We're excited about you because you have… B.S. or M.S. in Computer Science or equivalent. 10+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production. Proficiency in using AI coding tools (e.g., Claude Code) in th

We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is understood, trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continue to grow—driven by advances in AI, new creation tools, and emerging content formats—we’re investing in intelligent systems that can understand, evaluate, manage, and route content reliably at global scale. We’re hiring Senior Staff Machine Learning Engineers to build and scale foundational ML systems that power content understanding, safety, policy enforcement, and decisioning across Spotify. Depending on your experience and interests, you may focus on areas ranging from multimodal content understanding and platform-level ML systems to safety, risk detection, policy enforcement, and compliance. You’ll help shape the architecture and technical strategy behind how Spotify understands and makes decisions about content at global scale. This work is foundational to delivering safe, high-quality experiences for listeners and creators while enabling new ways for people to interact with content across Spotify. What Yo

We design Spotify’s consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. The Content Platform team powers the full lifecycle of content across music, podcasts, audiobooks, and emerging formats at Spotify. We ensure that everything from licensed catalog to user-generated content is understood, trusted, safe, and high quality for millions of listeners worldwide. Our systems are responsible for how content is ingested, understood, enriched, governed, and distributed across the platform. As the scale and diversity of content continue to grow—driven by advances in AI, new creation tools, and emerging content formats—we’re investing in intelligent systems that can understand, evaluate, manage, and route content reliably at global scale. We’re hiring Senior Staff Machine Learning Engineers to build and scale foundational ML systems that power content understanding, safety, policy enforcement, and decisioning across Spotify. Depending on your experience and interests, you may focus on areas ranging from multimodal content understanding and platform-level ML systems to safety, risk detection, policy enforcement, and compliance. You’ll help shape the architecture and technical strategy behind how Spotify understands and makes decisions about content at global scale. This work is foundational to delivering safe, high-quality experiences for listeners and creators while enabling new ways for people to interact with content across Spotify. What Yo

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Who We Are: The Machine Learning Platform team at Reddit is a high-impact team that owns the infrastructure that powers recommendations, content discovery, user and content quantification, while directly impacting other teams such as Growth, Ads, Feeds, and Core Machine Learning teams. What You’ll Do: As a Senior Staff Software Engineer, you will help define and lead the vision for Reddit’s large-scale GenAI Platform, shaping the strategy, architecture, and operating model that enable teams across the company to build, deploy, and scale generative AI products with confidence. Contribute to the design, implementation, and maintenance of the LLM Gateway, focusing on features like unified API endpoints for internal/externally hosted LLM, rate/token limit management, and intelligent failover mechanisms to boost uptime and reliability. Lead and execute the vision, strategy, and roadmap for Reddit’s large-scale GenAI Platform. Define the platform architecture and operating model that enable teams to build, deploy, and scale GenAI products reliably. Drive the strategy for a unified LAG Gateway supporting internally and externally hosted LLMs through consistent APIs and abstractions. Set the direction for core platform capabilities such as rate and token limit management, intelligent failover, and production resilience. Shape Reddit’s approach to an enterprise-grade RAG system Establish the strategic direction for agentic AI workflows and tool-use patterns across the platform. Own the end-to-end platform strategy from concept t

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

This role in the Offline Driving Intelligence team is responsible for developing/learning behavior models for road users such as cars, bicycles, and pedestrians. These agents populate Zoox's simulations and must be indistinguishable from real road users, yet fully controllable: promptable into the rare, adversarial, safety-critical behaviors we need to test against. This means the team’s models directly impact how fast Zoox can train, validate and ship its driving stack. Our team collaborates closely with Planner, Simulation and Validation teams to develop and validate our driving performance. As an ML Agents Machine Learning Engineer, you will work on the bleeding edge of the industry, developing novel machine learning pipelines and models to predict the behavior of other agents in the world and planning the best course of action for the ego vehicle. In this role, you will... Develop new deep learning models that use imitation learning and reinforcement learning to generate driving plans for human-like driving agents. Work on novel techniques to estimate the quality of those driving plans along the dimensions of safety, progress, comfort and realism. Build generative behavior models (e.g. autoregressive, diffusion) that are conditionable on scenario intent — "cut off the ego vehicle," "jaywalk here" — for targeted stress-testing. Leverage our compute, infrastructure and large corpus of data to push boundaries of the field. Develop metrics and tools to analyze errors and understand improvements of our systems. Collaborate with engineers on Perception, Planning, Simulation, and Validation to solve the overall Autonomous Driving problem. Qualifications PhD degree in computer science or related field and 4+ years of relevant professional experience or master's degree and 7+ years of relevant professional experience

Our Perception team is responsible for using our sensor data to understand the complex and dynamic environments where we drive. In this role, you will have access to the best sensor data in the world and an incredible infrastructure for testing and validating your algorithms. We are creating new algorithms for segmentation, tracking, classification, and high-level scene understanding, and you could work on any (or all!) of these components. As a Senior Staff ML Engineer, you will lead the development of machine learning algorithms that can range in influence from onboard autonomy to offboard autonomy and validation. You will collaborate closely with other teams specializing in Prediction, Planning, Simulation, and Safety Validation, influencing our overall technical stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. The impact of the role can be in the form of impacting immediate company milestones to leading forward-looking exploratory projects. Responsibilities Develop new algorithms to understand the scene around the robot, and how that scene would evolve through time Build multi-modal foundation models for on-vehicle and offline applications Develop new algorithms to apply generative AI to simulation to improve the realism of our offline validation systems Leverage our large-scale machine learning infrastructure to discover new solutions and push the boundaries of the field Provide technical mentorship to the broader group of ML developers at Zoox Collaborate with engineers on Prediction, Planning, and Simulation to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Experience with training and deploying Deep Learning models on sensor data-Experience

#Team Nextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com . Meet Your Future Neighbors At Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform, including newsfeed, notifications, ad relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be integral to making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live. At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we’re looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs. We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London. The Impact You’ll Make You will be part of a scrappy and

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index

Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About the Role We are looking for a Senior/Staff Machine Learning Engineer to be a technical leader on Nuro’s Behavior & Planning team. Our team owns how the Nuro Driver behaves on the road: prediction, decision making, and planning, and is responsible for turning Nuro’s large-scale driving data into safe, comfortable, and natural driving behavior. In this role you will bring strong, general machine learning expertise to some of the hardest problems in autonomy and drive them from research through to deployment on real vehicles. You’ll work at the frontier of applied ML spanning areas such as foundation and world models, LLM/VLM reasoning, reinforcement and imitation learning, generative and diffusion models, and transformer-based prediction and planning. You’ll apply this knowledge and experience to make our driving generalize as we scale across new geographies as we expand throughout the U.S. and globally, and across new vehi

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

The Autonomy Behaviors team is responsible for producing our vehicle’s driving trajectory. As a Principal ML Engineer, you will lead the technical development of machine learning algorithms for our next-generation ML Planner. Your impact will range from delivering innovations for immediate milestones to pioneering exploratory projects. You will collaborate closely with teams specializing in Foundation Models, Perception, Simulation, and Safety Validation, in influencing our autonomy stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. In this role, you will: Set the technical direction of ML development for the future of our Planner Push the frontiers of imitation learning, reinforcement learning, and model scaling to develop new ML models for our onboard Planner Identify and drive force-multipliers for ML development, including metrics, data, and training frameworks Develop new methods to leverage Zoox’s Foundation Models into the ML Planner Provide technical mentorship to the broader group of ML developers at Zoox Collaborate with engineers across Autonomy Software, Simulation, System Design and Mission Assurance, and other departments to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Proven track record of technical leadership in large-scale AI organizations Significant experience with training and deploying Deep Learning models to production Fluency in C++ or Fluency in Python with a basic understanding of C++ Extensive experience with programming and algorithm design-Strong mathematics skills, 10+ years of experience Bonus Qualifications Conference or Journal publications in Machine Learning or Robotics related v

We design Spotify's consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. You'll lead a senior-heavy group of 10–12 machine learning engineers, including Staff engineers, who team up dynamically to solve high-priority business problems while staying deep in content understanding (audio, video and text). This is a player-coach role with a strong strategic remit: you'll shape where the group goes next, grow our audio understanding expertise over the long term, and help the team scale through thoughtful, practical use of AI in everyday engineering work. What You'll Do Lead, coach and grow a group of 10+ senior and Staff machine learning engineers who team up dynamically around business problems while staying deep in their domain. Set technical and team strategy for multiple content understanding problems and turn it into clear, achievable plans. Own delivery of high-priority company initiatives, from shaping the problem through to measurable impact for listeners. Stay close to the technology as a player-coach. Lead technical strategy, reviewing designs, guiding modelling and retrieval choices, and contributing hands-on where it helps the team most. Define and champion a practical point of view on how ML engineers use AI tools in their day-to-day work, and help the team realise real productivity gains. Partner with product, design, research and other engineering leaders across Spotify