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Senior Staff Machine Learning Engineer Jobs in California

PayPal

Senior Staff Machine Learning Engineer

San Jose, CA · On-site

$143K - $189K/yr

PayPal, Inc. seeks Senior Staff Machine Learning Engineer in San Jose, CA Job Duties: Define and drive the strategic vision for implementing machine learning (ML) functions into the software ...

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Intuit

Staff Machine Learning Engineer

Mountain View, CA · On-site

$202K - $274K/yr

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA

$202K - $274K/yr

Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected to help ...

Intuit

Staff Machine Learning Engineer

Mountain View, CA · On-site

$202K - $274K/yr

Overview Come join Intuit as a Staff Machine Learning Engineer! In this role, you'll work alongside AI scientists and machine learning engineers to create AI-powered experiences. You'll be expected ...

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All JobsStaff Machine Learning Engineer JobsSenior Staff Machine Learning Engineer JobsSenior Staff Machine Learning Engineer Jobs in California

Senior Staff Machine Learning Engineer information

See California salary details

$58.7K

$124.9K

$181.1K

How much do senior staff machine learning engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for senior staff machine learning engineer in California is $124,900.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,100.00 and $141,600.00 per year, depending on experience, location, and employer.

What are the primary challenges a senior staff machine learning engineer faces when leading large-scale ML projects?

Senior Staff Machine Learning Engineers often navigate complex challenges such as aligning cross-functional teams, ensuring model scalability, and maintaining data integrity across evolving pipelines. They are responsible for setting technical direction, mentoring junior engineers, and driving collaboration between data scientists, software engineers, and product managers. Balancing hands-on technical work with high-level architectural decisions, while also keeping up with rapid advancements in the field, is key to success in this role.

What does a senior staff machine learning engineer do?

A Senior Staff Machine Learning Engineer leads the design, development, and deployment of complex machine learning systems within an organization. They work closely with cross-functional teams to identify business challenges that can be addressed with machine learning and guide the technical strategy for implementing solutions. Their responsibilities often include mentoring junior engineers, setting best practices, overseeing large-scale projects, and ensuring models are robust, scalable, and ethically implemented. Additionally, they may contribute to research and development, staying up-to-date with the latest advancements in the field.

What is the difference between Senior Staff Machine Learning Engineer vs Machine Learning Engineer?

AspectSenior Staff Machine Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's/PhD in CS, AI, or related; experience in ML frameworksBachelor's/Master's in CS, AI, or related; some experience in ML
Work EnvironmentLeadership roles, cross-team collaboration, strategic planningImplementation, model development, experimentation
Industry UsageTech companies, research labs, large enterprisesStartups, tech firms, research projects

The Senior Staff Machine Learning Engineer typically holds a more senior, strategic role with leadership responsibilities, while the Machine Learning Engineer focuses on developing and deploying ML models. Both roles require strong technical skills, but the senior position involves guiding projects and mentoring teams.

What are the key skills and qualifications needed to thrive as a senior staff machine learning engineer, and why are they important?

To thrive as a Senior Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, software engineering, and a relevant advanced degree (often MS or PhD). Mastery of tools such as Python, TensorFlow, PyTorch, distributed computing frameworks, and experience with cloud platforms is typically required. Strong leadership, communication, and project management skills distinguish top performers in this role. These abilities are crucial for designing scalable ML solutions, leading teams, and driving impactful business outcomes.
What are popular job titles related to Senior Staff Machine Learning Engineer jobs in California? For Senior Staff Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Senior Staff Machine Learning Engineer jobs in California look for? The top searched job categories for Senior Staff Machine Learning Engineer jobs in California are:
What cities in California are hiring for Senior Staff Machine Learning Engineer jobs? Cities in California with the most Senior Staff Machine Learning Engineer job openings:
Senior Staff Machine Learning Engineer jobs near you
Infographic showing various Senior Staff Machine Learning Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 25% Part Time, 3% Temporary, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $124,900 per year, or $60 per hour.

Senior/Staff Machine Learning Engineer

Dexterity

Redwood City, CA • On-site

$127K - $175K/yr

Full-time

Re-posted 8 days ago

Job description

About Dexterity
At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work.

We're starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses worldwide. Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven and hardware-agnostic and have already picked 100+ million goods in production. And did we mention we're customer-obsessed? Every decision, large and small, is driven by one question - how can we empower our customers with robots to do more than they thought was possible?

Dexterity is one of the fastest-growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures. We're a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality!

About the Role
As a Senior/Staff Machine Learning Engineer, you will be working on a myriad of challenges related to robot task and action planning. You will leverage techniques from machine learning to solve hard sequential decision problems that require reasoning about the physical world and its dynamics. You will also stay abreast of the latest progress in imitation learning, reinforcement learning, and other related fields in order to further develop Dexterity's technology foundations in Physical AI. Additionally, you will be responsible for updating and scaling our current ML pipelines to cover more scenarios and improve accuracy.

Dexterity's robotic solutions integrate data from a multitude of sensors, including RGB cameras, depth sensors, force-torque sensors, encoders, system telemetry and human input. To better inform the planning algorithms, you may work on sensor fusion and state estimation techniques to leverage this multimodal sensory data.

You will also work closely with the data platform, physics simulation, and robot operations teams to develop effective and efficient ways to improve the system's internal world model.

Dexterity has an expanding set of algorithmic challenges as we deploy new robotic applications, including areas such as:

- Improving packing algorithms to build taller, denser, more stable structures with a wider variety of objects.
- Solving the logistics task of moving and sorting inventory throughout a warehouse.
- Building models that understand physics and geometry for both short- and long-horizon tasks.

In addition to curating datasets and developing/improving machine learning models, you will be responsible for building data flywheels. Ideally, you will bring data-driven productization experience and help the team broadly in qualifying, deploying and updating models.
Responsibilities
  • Design and implement machine learning solutions across Dexterity's robotics stack, including but not limited to perception, decision-making, action scoring, and predictive modeling
  • Own the full ML development cycle for these solutions: data curation, labeling, training, evaluation, deployment, and iteration
  • Build performant training and inference pipelines using PyTorch, with production-readiness and scalability in mind
  • Collaborate closely with robotics, data platform, and simulation teams to integrate ML into real-time, latency-sensitive robotic systems
  • Use profiling, monitoring, and experiments to optimize model performance and reliability
  • Ensure reproducibility, traceability, and modularity across training and serving pipelines
  • Maintain clean, production-quality code in Python (and C++ where required)
  • Help establish best practices for model versioning, dataset management, and ML operations
Required Skills
  • Degree in Computer Science, Electrical Engineering, or Mathematics 5+ years of industry experience applying machine learning to real-world, production systemsStrong Python skills and deep experience with PyTorch
  • Ability to work fluently across ML tasks, e.g., classification, regression, ranking, segmentation, and structured prediction
  • Strong engineering background with experience profiling, debugging, and optimizing model and pipeline performance
  • Proven ability to design and maintain reliable systems, from model training to field deployment
  • Experience with cloud-based infrastructure (AWS, GCP, Azure) and containerized environments (Docker)
  • Familiarity with Linux, Git, CI/CD) and software development best practices (unit/acceptance/integration testing, code reviews)
Nice to haves
  • Prior experience in robotics, autonomous systems, or real-time ML applications
  • Exposure to multimodal data (e.g., RGBD, force-torque, pose estimates, telemetry)
  • Experience deploying models using serving stacks like NVIDIA Triton, TorchServe, or custom low-latency frameworks
  • Background in computer vision, geometric learning, or time-series modeling
  • Experience with Kubernetes, Ray or other distributed training and inference systems
  • Previous startup experience or experience in fast-paced, cross-disciplinary environments
$170,000 - $225,000 a year
Our Total Rewards philosophy is designed to recognize contributions toward meaningful innovation. Base pay is one component of a broader compensation package that may include equity grants, benefits, and other incentives, depending on role and eligibility.

For this position, the expected base salary range is $170,000 to $225,000 annually. Actual compensation will be determined based on skills, experience, education, and market factors, and may vary accordingly.

Final compensation decisions are made individually and take a number of factors into consideration. Eligible employees may be considered for equity awards as part of their overall compensation. Access to benefits and wellness resources is provided in accordance with company policies and may vary based on role and location.

Equal Opportunity Employer
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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