Senior Staff Machine Learning Scientist Jobs

Our Mission You call. You wait. You call again. In every other part of your life, you book in seconds. In healthcare, you’re blocked. We’re here to give power to the patient. For nearly 20 years, we’ve built the leading healthcare marketplace - helping tens of millions of people find and book the care they need. Now, we’re going further: building our infrastructure beyond Zocdoc’s marketplace to power access to care wherever patients search, from provider websites and insurance directories to search engines, AI platforms, and more. Healthcare still lacks something every other major consumer industry takes for granted: a seamless way to go from seeking to getting . We don’t want to own the front door to care; there isn't one. We want to make sure all of those doors open when patients are knocking. Fixing healthcare starts with fixing access to it. And we're still just getting started. Your Impact on our Mission Zocdoc's mission is simple and hard: give power to the patient. We are the nation's leading digital healthcare marketplace — connecting millions of patients to the right care, faster than ever. The Data & Analytics team is at the center of how Zocdoc grows, evolves, and makes high-stakes decisions at scale. As a Sr/Staff Data Scientist you will be one of the most senior analytical voices at the company — a strategic thought partner to directors and senior leadership across Product, Marketing, Sales, Finance, Revenue, Operations, Customer Experience, and Platform. You'll work on some of Zocdoc's most complex and ambiguous business problems — where the question itself isn't always defined, and the right method doesn't fit neatly into a playbook. You'll lead the analytical strategy, apply rigorous experimentation and causal inference frameworks at scale, and turn structured thinking into decisions that shape how Zocdoc grows. This is a high-visibility, high-impact individual contributor role. Success here is measured not just by the q

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Staff Data Scientist - Experimentation & Measurement Overview: As a Staff Data Scientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of key initiatives and programs. You’ll help shape how millions of players around the world experience PlayStation by bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across the company. This highly visible role will advance our experimentation practices and ensure that data-driven insights inform the way we build, market, and evolve our products. What You’ll Be Doing: Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn’t feasible. Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company’s senior leadership. Mentor and guide other Data Scientists, providing thought leadership and technical direction. Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication. Help define a

Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Staff Data Scientist - Experimentation & Measurement San Mateo, CA (Hybrid) Overview: As a Staff Data Scientist on the Decision Science team at PlayStation, you will take a leading role in designing and interpreting experiments that evaluate the impact of key initiatives and programs. You’ll help shape how millions of players around the world experience PlayStation by bringing statistical rigor, clear measurement strategies, and deep causal inference expertise to some of the most critical initiatives across the company. This highly visible role will advance our experimentation practices and ensure that data-driven insights inform the way we build, market, and evolve our products. What You’ll Be Doing: Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn’t feasible. Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company’s senior leadership. Mentor and guide other Data Scientists, providing thought leadership and technical direction. Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results commu

Scale is hiring a Senior Product Designer / Founding Designer to lead product design for Scale’s rapidly growing ‘AI for Enterprise Data’ business unit. The mission of AI for Enterprise Data is to accelerate the deployment of AI by helping large enterprises solve their most ambitious challenges. This role will take on multiple products ranging from 0-1 initiatives to improving established products. This includes a suite of powerful AI tools for insurance AI, document processing, and more. Responsibilities Design end to end user flows, wireframes, high-fidelity mockups, and interactive prototypes for desktop web applications. Partner with Product Managers, Engineers, Data Scientists, and Operations team members to solve product and business challenges. Advocate for the voice of the user as the founding designer of the business unit. Prioritize and execute work in a fast paced environment with rapid timelines and high amounts of scope and ambiguity. Contribute to the evolution of our company-wide design system and interaction patterns. Take ownership to identify product gaps and rally support for proposed solutions. Qualifications Experience leading end-to-end B2B and enterprise web applications. Extremely high proficiency in Figma, fast execution speed is a must. Experience designing dashboards, data visualization, domain-specific editors, and forms. Understanding of front-end development processes for web interfaces. Strong communication and collaboration skills, including customer-facing meetings. Portfolio of product design projects that highlight your diversity of skills. Nice-to-haves Exposure to artificial intelligence, machine learning, and other technical concepts. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. The Firmware & Product Test (FPT) team at Micron Technology holds a pivotal role in validating firmware specifications for SSDs. The team develops comprehensive verification plans, implements them using Python, and ensures strict alignment to NVMe standards and security protocols. Validation occurs across multiple environments, including simulation, FPGA prototyping, and prototype hardware. Summary of the Role The Engineer (E4) in the Firmware & Product Testing (FPT) team supports the validation of enterprise SSD firmware through test development, automation, execution, and failure analysis. This role focuses on NVMe front-end features and customer specifications while applying Python-based automation and data-driven techniques to improve test efficiency and product quality. Working closely with firmware test engineers, senior mentors, and data scientists, the engineer gains hands-on experience at the intersection of firmware validation and AI/ML, contributing to more effective and scalable testing methodologies. Responsibilities: Develop and implement firmware verification plans for customer requirements and NVMe protocol features, including SMART, Trim, Get Log Page, and OCP Analyze regression and validation failures, perform root-cause analysis, and communicate findings and mitigation plans Develop and enhance test automation, reporting, and data-collection tools within established validation frameworks Leverage AI-assisted tools, LLMs, and agent-based solutions

Location Details: At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely. This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. GoDaddy is not currently considering candidates for this role in California, Seattle, or NYC. Join Our Team... At GoDaddy, we're building the next generation of AI and machine learning capabilities that power experiences for millions of entrepreneurs worldwide. Our Machine Learning Engineering team bridges the gap between research and production, transforming cutting-edge models into scalable, reliable, and observable services that operate at global scale. We're looking for a Staff Software Engineer to lead the design and evolution of the infrastructure, platforms, and services that enable machine learning models to run in production. This is a highly technical, hands-on role where you'll work closely with ML Scientists, Data Engineers, and Product teams to deliver robust ML-powered solutions while helping shape the future of our machine learning platform. As a senior technical leader, you'll influence architecture, drive engineering excellence, and mentor engineers across a globally distributed team. What you'll get to do... Experience deploying and operating machine learning or generative AI workloads using technologies such as vLLM, Triton, TorchServe, SageMaker Endpoints, or similar serving frameworks. Familiarity with modern observability practices and tools including OpenTelemetry, Prometheus, Grafana, and CloudWatch. Experience with vector databases, feature stores, caching technologies (Valkey/Redis), and infrastructure-as-code solutions

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Payment Success helps merchants get paid and keep their cash flow reliable. We predict which payments are likely to fail, recover the money when they do, and protect merchant cash flow across our payment rails. As Engineering Manager, you will lead a cross-functional team of engineers, a designer and data scientists, building intelligent products that use machine learning and AI. You will take ownership of the payment intelligence products we have already built, and work with your team and product manager to decide what we build next. We give teams problems to solve rather than tasks to complete, so you and your team will own what gets built, how it gets built and how success is measured. You will be accountable for the quality, delivery and operation of everything the team ships, and you will look after your people through 1:1s, feedback and career development. You'll step in wherever the team needs you, and earn credibility with senior engineers and data scientists within the team and across product development. What excites you Shipping stuff: you’ll work with your tea

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Payment Success helps merchants get paid and keep their cash flow reliable. We predict which payments are likely to fail, recover the money when they do, and protect merchant cash flow across our payment rails. As Engineering Manager, you will lead a cross-functional team of engineers, a designer and data scientists, building intelligent products that use machine learning and AI. You will take ownership of the payment intelligence products we have already built, and work with your team and product manager to decide what we build next. We give teams problems to solve rather than tasks to complete, so you and your team will own what gets built, how it gets built and how success is measured. You will be accountable for the quality, delivery and operation of everything the team ships, and you will look after your people through 1:1s, feedback and career development. You'll step in wherever the team needs you, and earn credibility with senior engineers and data scientists within the team and across product development. What excites you Shipping stuff: you’ll work with your tea

About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. The role Payment Success helps merchants get paid and keep their cash flow reliable. We predict which payments are likely to fail, recover the money when they do, and protect merchant cash flow across our payment rails. As Engineering Manager, you will lead a cross-functional team of engineers, a designer and data scientists, building intelligent products that use machine learning and AI. You will take ownership of the payment intelligence products we have already built, and work with your team and product manager to decide what we build next. We give teams problems to solve rather than tasks to complete, so you and your team will own what gets built, how it gets built and how success is measured. You will be accountable for the quality, delivery and operation of everything the team ships, and you will look after your people through 1:1s, feedback and career development. You'll step in wherever the team needs you, and earn credibility with senior engineers and data scientists within the team and across product development. What excites you Shipping stuff: you’ll work with your tea

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Member of Technical Staff in the Safety for Agents team, you will make a meaningful impact on the development of better, fairer, more trustworthy, and more secure Large Language Models (LLMs). Your primary focus will be on data generation, post-training algorithms, and evaluation methods to ensure Safety in the next generation of models that can access external resources and take actions in the world. You will work closely with other cross-functional machine learning teams and data annotation teams, and will also collaborate with product and policy teams. This role combines expertise in machine learning, ethical and responsible AI, experimental design, and data generation and management. It will require curiosity to tackle totally new scientific problems, engineering skills to implement the pieces we need to test solutions to these, and a desire to dive into messy data and results. You will be on a small team with a lot of autonomy and decision-making power, responsible for making the next generation of LLMs better for society as a whole. Please Note: The existing team work in offices in London, Edinburgh, Pa

The Zoox 3D Sensor Simulation team’s work is at the core of creating in-the-loop simulation and high fidelity synthetic data for training and testing autonomous vehicle AI. We are looking for a machine learning professional with experience applying ML to sensor data, such as LiDAR, radar, and cameras. This role lies at the intersection of machine learning and 3D simulation at Zoox, ranging from learned sensor models to neural 3D reconstruction. By improving the realism of simulated sensors (lidar, radar, and cameras), you’ll enable the Zoox robotics autonomy stack to learn, improve, and enhance the mobility of humans. In this role, you will: Design, train, and validate ML models that improve the realism of simulated lidar, radar, and camera data in autonomous vehicle (AV) simulation pipelines. Collaborate with Synthetic Data and HIL Sim teams to integrate 3DGS and NeRF-based 3D reconstruction with simulation of all sensor modalities. Build and curate training datasets from real and simulated sensor data, including GenAI-based data augmentation. Partner with Sim V&V and Perception engineers to define sensor realism metrics and close the sim-to-real gaps with the greatest impact on autonomy. Mentor engineers and interns, and establish best practices for training and deploying ML on Zoox sensor data. Qualifications: 2+ years of prior experience as a Technical Lead 5+ years of experience developing ML models in Python with PyTorch or TensorFlow <

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 . We’re looking for a Senior Staff Machine Learning Engineer to lead Reddit’s next-generation user understanding initiative: building a unified, high-fidelity representation of each user that powers personalization across the platform. This role requires deep expertise in mainstream ML user modeling approaches (e.g., large-scale embeddings, user interest modeling, affinities, behavioral signals) and the ability to reimagine these systems in the GenAI era—leveraging LLMs and foundation models to unlock step-change improvements in fidelity, adaptability, and expressiveness. You will set the technical direction for this space, leading the design and implementation of Reddit’s core user representation layer—spanning embeddings, interest modeling, and key user attributes. You’ll ensure this foundation is scalable, reliable, and widely adopted across Feeds, Search, Notifications, and Ads, partnering closely with product, infrastructure, and downstream ML teams to drive measurable impact. This is a high-impact role. The systems you build will shape how hundreds of millions of people experience Reddit every day—what they see, what they discover, and the communities they connect with. Your work will directly advance personalization and relevance at global scale, strengthening Reddit as a platform for meaningful connection and belonging. What you'll do: Design User Understanding Strategy: Define a unified user understanding framework and strategy: how users are represented (embeddings, tags, attributes, LLM-based user profile), how

Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 200+ public data centers globally and thousands of private sites at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform. We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler. Role We are looking for a Senior Staff Machine Learning Engineer to join our team. This is a remote (USA) role, reporting to the Manager AI Platform and Data Science in the AI Platform and Data Science department. This team’s mission is high-fidelity risk identification in customer data, with goals to catch all threats while minimizing noise. To achieve this, you will develop solutions applying data analysis and threat-research while leveraging AI, machine learning, and data engineering to build quality, data-driven components to automate security analysis. What you’ll do (Role Expectations) Translate risk identification methods into agent logic, understanding the benefits and limitations of agents and ensuring quality across risk analysis, explanations, and recommendations Collaborate closely with threat-research to understand data, threats, and their approach to developing security heuristics Identify and solve data requi

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 . About the Role: We are seeking a Senior Staff Machine Learning Engineer to define and accelerate how we leverage agentic AI to transform machine learning models and modeling workflows. This high-impact role focuses directly on modeling leverage —enhancing model quality and velocity—rather than building general infrastructure. As a senior staff engineer, you will operate as a technical leader across the entire modeling loop, utilizing modern AI-assisted development systems (such as Claude, Cursor, and comparable tools) to make model development faster, more rigorous, and significantly more effective across the organization. Why Join Us? This role offers a domain-flexible platform to redefine how ML engineering is done. If you are passionate about combining deep ML fundamentals with the vanguard of agentic AI to multiply team impact, we’d love to talk to you. What you’ll do: Develop advanced ML models and the agentic workflows that help teams design, train, evaluate, and improve them. Use tools such as Claude, Cursor, and comparable AI-assisted development systems to investigate model behavior, generate and test hypotheses, automate repetitive analysis, and improve code and experiments. Build reliable loops for data and label analysis, feature and embedding development, architecture comparison, hyperparameter optimization, error analysis, and experiment readouts. Design evaluation harnesses that measure both model outcomes and agent/workflow quality, including correctness, reproducibility, regressions, cost, a

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 . Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence About Reddit Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and 101M+ daily active unique visitors, we’re one of the largest sources of conversation and knowledge on the internet. For more information, visit redditinc.com . Team Overview The Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate. Our systems help ML engineers move faster across the full development lifecycle: creating features, generating training data, running offline experiments, validating model quality, launching production models, and operating ML systems reliably. We are looking for a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus will be on the feature development and training iteration loop: making it faster and easier for ML engineers to build features, generate reliable training data, run experiments, and move from idea to validated model improvement. Over time, this scope will expand into serving and online experimentation workflows, creating