Staff Senior 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

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 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

Machine Learning Engineer – Biometrics (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestra

Role Purpose We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on ex

Machine Learning Engineer – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like A