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Senior Machine Learning Engineer Jobs in California

Hum AI

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Senior Machine Learning Engineer Location: San Francisco About Hum.ai Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building. Join us ...

Yum! Brands

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Yum Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

KFC Corporation

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash ...

Warnerbros

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

Warnerbros

Senior Machine Learning Engineer

Burbank, CA

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in California

Senior Machine Learning Engineer information

See California salary details

$58.7K

$124.9K

$181.1K

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

As of Sep 15, 2026, the average yearly pay for senior 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 does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in California?

The most popular types of Machine Learning Engineer jobs in California are:

What are popular job titles related to Senior Machine Learning Engineer jobs in California?

For Senior Machine Learning Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Senior Machine Learning Engineer jobs in California look for?

The top searched job categories for Senior Machine Learning Engineer jobs in California are:

What cities in California are hiring for Senior Machine Learning Engineer jobs?

Cities in California with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $124,900 per year, or $60 per hour.

Senior Machine Learning Engineer

San Francisco, CA • On-site

Hum AI
See more jobs at Hum AIexternal

$123K - $169K/yr

Full-time

Re-posted 9 days ago

Job description

Senior Machine Learning Engineer
Location: San Francisco
About Hum.ai
Hum.ai is building planetary superintelligence. Backed by top funds, we've raised $10M+ and are now heads down building.
Join us at the cutting edge, where we're scaling generative transformer diffusion models, designing next-gen benchmarks, and engineering foundation models that go far beyond LLMs. You'll be at the core of a moonshot journey to define what's next in agentic AI and frontier model capabilities.
We are looking for an experienced Senior Machine Learning Engineer who is eager to advance the frontier of AI, help us design, build, and scale end-to-end novel foundation models, and leverage their hands-on experience implementing a wide range of pre-training and post-training models, including large foundation models (beyond just LLM fine-tuning).
This role is focused on:
  • Designing, implementing, and scaling state-of-the-art models
  • Productionizing research codes, models and technologically complex systems
  • Shaping benchmark design and model evaluation frameworks
  • Building agentic AI capabilities and long-term technical bets

Who are we?
Hum is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we're backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations.
What do we do?
We're building multimodal foundation models for the natural world. We believe there's more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world.
About the role
The role will involve:
  • Collaborating with researchers and scientists to implement, evaluate and scale proof-of-concept models.
  • Owning, implementing and integrating the latest state-of-the-art methods and external open-source codes.
  • Develop AI systems capable of accurately understanding the universe and generating new knowledge.
  • Training multi-modal models supporting different sensor and other modalities like text

Requirements
  • Bachelor's degree in computer science, engineering, a related field, or equivalent experience.
  • 5+ years of relevant work experience.
  • Prior experience building distributed training pipelines for multi-node systems using PyTorch and Ray.
  • Experience training large diffusion or transformer models. Preferably on video or time series data.
  • Proficiency with Python, Ray Trainer, PyTorch, and Anyscale framework.
  • Familiarity with cloud platforms such as AWS, GCP, or Azure.

Nice to have
  • Past training of video or time-series models
  • Startup experience, comfortable with a small dynamic team.
  • Location wise, strong preference for in-person in Waterloo or San Francisco however remote work is possible for exceptional candidates.

Apply