Staff ML Engineer Jobs
Staff ML Engineer jobs are open across technology, finance, healthcare, and autonomous systems, from senior individual contributor to principal and distinguished levels, with specializations in large-scale model training, MLOps infrastructure, and recommendation systems. See the openings below and apply to the ones that match your experience.
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Showing 5 of 316+ Staff ML Engineer jobs
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Pittsburgh, PA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience leading ML design and optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
- 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
- Experience building and architecting ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
- Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience in Machine Learning modeling, specifically with Large Language Models (LLMs).
- Experience in distributed Machine Learning system design.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Research emerging technology and make trade-off decisions between immediate wins and long-term stability.
- Modify training and serving infrastructure to support new modeling techniques and products.
- Collaborate closely with team members and partners to build systems that integrate seamlessly across the ecosystem.
- Improve robustness, reliability, and usability of machine learning infrastructure.
- Engage with modeling teams to explore pain points and identify novel use cases.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Pittsburgh, PA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience leading ML design and optimizing end-to-end Machine Learning (e.g., model deployment, model evaluation, data processing, debugging).
- 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
- Experience building and architecting ML systems and infrastructure (e.g., for model training, evaluation, deployment, serving).
- Experience designing and operating distributed computing systems for large-scale AI/ML workloads.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience in Machine Learning modeling, specifically with Large Language Models (LLMs).
- Experience in distributed Machine Learning system design.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Google Ads is at the forefront of AI innovation, applying cutting-edge machine learning and Generative AI models like Gemini to power a multi-billion dollar global business.
Our work directly impacts billions of users by protecting users from harm, improving ad quality, and optimizing campaigns for advertiser return-on-investment. We foster a culture of deep collaboration, partnering closely with teams like Google Research and DeepMind to solve complex challenges. Join us to work on state-of-the-art AI, take on problems at an unparalleled scale, and build the next generation of advertising technology.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Research emerging technology and make trade-off decisions between immediate wins and long-term stability.
- Modify training and serving infrastructure to support new modeling techniques and products.
- Collaborate closely with team members and partners to build systems that integrate seamlessly across the ecosystem.
- Improve robustness, reliability, and usability of machine learning infrastructure.
- Engage with modeling teams to explore pain points and identify novel use cases.
See All 316+ Staff ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Staff ML Engineer JobsStaff ML Engineer Job Market
Who's Hiring
- Uber27
- ServiceNow23
- Apple19
- GEICO12
- Google11
Top Industries Hiring
- Technology & Software58
- Insurance10
- Artificial Intelligence9
- Automotive4
- Hospitality & Tourism4
What Employers Look For
The qualifications that appear most often in staff ML engineer jobs.
- 7 or more years of machine learning or applied research experience with production deployments
- Deep proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
- Experience designing and operating large-scale distributed training and inference systems
- Strong background in MLOps, including model monitoring, feature stores, and CI/CD pipelines
- Demonstrated ability to mentor engineers and influence technical direction across multiple teams
- Advanced degree in computer science, statistics, or a related quantitative field
Tips for Your Staff ML Engineer Job Search
Quantify model impact on your resume
Hiring managers for staff-level roles want to see scale and outcome, not just tools. Replace 'built a recommendation model' with the reduction in latency, lift in engagement, or revenue impact your system drove. Numbers make a staff-level scope immediately clear.
Distinguish research from production on your resume
Staff ML engineers are expected to own systems end-to-end, not just prototype. Explicitly label each project as research, production, or both, and note team size and your decision-making authority. Ambiguity about scope is one of the most common reasons strong resumes get passed over.
Apply early to roles that fit
Migrate Mate lists staff ml engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target companies by ML maturity stage
A staff ml engineer at a seed-stage startup owns the entire ML stack solo. At a growth-stage company, you're building the platform others will use. At a large tech firm, you're coordinating across teams. Know which environment suits you before filtering your search, so you're applying to the right context.
Prepare a system design narrative for interviews
Staff-level ML interviews almost always include a large-scale system design question. Practice walking through feature engineering, model selection, serving architecture, and monitoring decisions in one coherent narrative. Interviewers are evaluating your ability to make and justify tradeoffs, not just recite ML concepts.
Negotiate scope alongside compensation
At the staff level, what you own matters as much as what you earn. During offer negotiation, ask which team you'll anchor to, what engineering headcount you'll influence, and what the 12-month roadmap looks like. Answers to those questions reveal whether the title matches the actual level of the role.
Staff ML Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most staff ml engineers?
The most active employers for staff ml engineers right now are Uber, ServiceNow, and Apple, and the most openings are in California, New York, and Washington, based on current listings on Migrate Mate as of November 2026. Demand is concentrated at companies running large-scale recommendation, search, or generative AI systems.
How many staff ml engineer jobs are remote?
About 64% of staff ml engineer openings are fully remote or hybrid as of November 2026, making it one of the more remote-accessible senior engineering roles. MLOps, platform engineering, and research-adjacent positions within the staff ML tier tend to have the highest share of fully remote arrangements compared to roles tied to real-time production systems requiring on-site collaboration.
How do you become a staff ml engineer?
Most staff ml engineers progress from senior ML engineer by demonstrating consistent ownership of cross-team technical decisions, not just individual project delivery. The clearest path is leading a high-impact production system from design through post-launch monitoring, earning trust as a technical voice across engineering and product, and building a portfolio of measurable improvements to model quality or infrastructure efficiency.
Can you get hired as a staff ml engineer without prior staff-level experience?
Yes, but you need to close the gap in how you present your work. Candidates who succeed at the staff level without a previous staff title typically have led a system used by multiple teams, made architectural decisions that outlasted their involvement, or mentored engineers who shipped meaningful features. Frame your resume around those outcomes, not your job title, and address scope and influence directly in your cover letter.
What does the staff ml engineer interview process look like?
Most staff ml engineer interview loops include a recruiter screen, a technical phone round focused on ML fundamentals or coding, a large-scale system design session, a cross-functional collaboration or leadership discussion, and a final round with senior engineering or research leadership. Some companies also include a take-home or presentation on past work. The system design and leadership rounds carry the most weight at the staff level.
Where can I find and apply to staff ml engineer jobs?
You can find and apply to staff ml engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background and apply directly to each one that fits.
See All 316+ Staff ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Staff ML Engineer Jobs