ZipRecruiter

Log In

1

Principal Machine Learning Engineer Jobs in California

AppFolio

Principal Machine Learning Engineer

Goleta, CA · On-site

Who We Are Looking For We're seeking a Principal Machine Learning Engineer to help define and lead the next generation of AI systems within Realm-X, and to drive AppFolio's long-term autonomous Real ...

next page

Showing results 1-20

All JobsPrincipal Machine Learning Engineer JobsPrincipal Machine Learning Engineer Jobs in California

Principal Machine Learning Engineer information

See California salary details

$73K

$145.3K

$209.7K

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

As of Jun 18, 2026, the average yearly pay for principal machine learning engineer in California is $145,292.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,900.00 and $170,700.00 per year, depending on experience, location, and employer.

What types of projects and responsibilities can a Principal Machine Learning Engineer typically expect in this role?

Principal Machine Learning Engineers are often tasked with leading the design, development, and deployment of large-scale machine learning models and systems that address key business challenges. In this role, you will collaborate closely with data scientists, engineers, and product managers to define project requirements, architect solutions, and ensure high-quality delivery. You may also guide research initiatives, oversee code and model reviews, and mentor junior engineers, helping to shape the technical direction of the team. Typical responsibilities can range from prototyping and optimizing algorithms to ensuring models are scalable, reliable, and aligned with organizational goals.

What are the key skills and qualifications needed to thrive in the Principal Machine Learning Engineer position, and why are they important?

To thrive as a Principal Machine Learning Engineer, you need advanced expertise in machine learning algorithms, statistical analysis, software engineering, and a strong background in computer science or related fields, often supported by a master's or PhD degree. Familiarity with tools such as Python, TensorFlow, PyTorch, cloud platforms (AWS, GCP, Azure), and relevant certifications strengthens technical capability. Leadership, strategic thinking, effective communication, and mentorship are vital soft skills for guiding teams and collaborating across departments. These competencies are essential for driving innovation, ensuring technical excellence, and influencing organizational AI initiatives.

What does a Principal Machine Learning Engineer do?

A Principal Machine Learning Engineer leads the design, development, and deployment of machine learning models and systems. They set technical strategy, mentor engineers, and collaborate with cross-functional teams to solve complex AI challenges. Their role often includes researching new algorithms, optimizing model performance, and ensuring scalability in production environments. Additionally, they work closely with data scientists, software engineers, and product managers to align ML initiatives with business objectives.

What engineers make $500,000?

Principal Machine Learning Engineers and senior AI specialists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can reach or exceed $500,000 in total compensation, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a strong track record, leadership responsibilities, and sometimes stock options or bonuses.

How much do principal AI engineers make?

Principal AI engineers typically earn between $130,000 and $200,000 annually, with salaries varying based on experience, location, and industry. They often have advanced skills in machine learning, deep learning, and data science, and may receive bonuses or stock options as part of compensation packages.

What is the salary of principal machine learning engineer?

The salary of a principal machine learning engineer typically ranges from $130,000 to $200,000 annually, depending on experience, location, and company size. Senior roles often include bonuses, stock options, and other benefits, reflecting the high level of expertise required in machine learning, data analysis, and software development tools.

Which 5 jobs will survive AI?

Principal Machine Learning Engineers are likely to continue playing a vital role as AI advances, focusing on developing and deploying complex models that require deep expertise in algorithms, data science, and software engineering. Jobs that involve creative problem-solving, strategic decision-making, and tasks requiring human judgment—such as healthcare professionals, educators, and skilled trades—are also expected to persist. Roles emphasizing emotional intelligence, interpersonal skills, and adaptability will remain resilient despite AI automation.
What are popular job titles related to Principal Machine Learning Engineer jobs in California? For Principal Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Principal Machine Learning Engineer jobs in California look for? The top searched job categories for Principal Machine Learning Engineer jobs in California are:
Principal Machine Learning Engineer jobs near you
Infographic showing various Principal Machine Learning Engineer job openings in California as of June 2026, with employment types broken down into 3% Internship, 82% Full Time, 6% Part Time, 3% Temporary, and 6% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $145,292 per year, or $69.9 per hour.

Principal Machine Learning Engineer

Edison Scientific Inc.

San Francisco, CA • On-site, Remote

$275K - $350K/yr

Other

Medical, Retirement

Posted 9 days ago

Job description

Principal Machine Learning Engineer

San Francisco, CA

About

Edison Scientific builds and commercializes AI agents for science. Scientific discovery moves too slowly, and autonomous AI agents are how we intend to fix that. We're assembling a team of top researchers and engineers across AI and biology to build an AI scientist.

Role

As a Principal Machine Learning Engineer at Edison Scientific, you play a central role in building the models and agents that accelerate scientific discovery. You will work on both cutting edge research and practical engineering, bridging advanced machine learning concepts with robust, reliable software that real scientists depend on.

This role is on-site at our San Francisco office in the Dogpatch neighborhood. Our office is a converted warehouse with high ceilings, open space, and a team excited about what we're building.

Responsibilities
  • Interpret qualitative challenges in building AI agents for science as well-formulated optimizable problems
  • Build appropriate environments in which to train and deploy AI agents that solve scientific tasks
  • Work with scientists to formulate training data pipelines, and scale them, ensuring observability and reproducibility
  • Lead training of large-scale LLM-based systems, including building internal infrastructure to improve the efficiency of experimentation and production training runs
  • Build efficient and flexible inference infrastructure, supporting complex sampling algorithms and custom architectures
  • Develop and extend our experimentation platform for internal tools and projects.
  • Collaborate closely with a multidisciplinary team of AI researchers, chemists, biologists, fostering an environment of innovation and discovery.
Qualifications
  • 8-10+ years of strong track record of work in applied ML research and application of ML methods to solving real-world problems
  • Experience working across the ML lifecycle: data pipelines and provenance, model training, model deployment, and validation in production systems.
  • Fluency in PyTorch, Jax or equivalent framework.
  • Demonstrated experience with experimentation in academic or industry settings.
  • Strong programming expertise with the capability to adapt to various technical challenges in the data, ML, and LLM software stack.
Bonus Points For
  • PhD in Machine Learning, Computer Science, or other quantitative field
  • Familiarity with leveraging and managing distributed computing resources
  • Background architecting complex distributed systems

Salary

$275,000 - $350,000 • Offers equity

Why join us?

  • Competitive salary and equity
  • Full healthcare coverage — we pay 100% of premiums for you and your dependents
  • Support for growing families, including a yearly new parent stipend and fertility coverage through Carrot
  • 401(k) company matching
  • $300 health and wellness benefit
  • Lunch is on us every day you're in the office, and dinner is on us when you're working late
  • Regular team offsites and company events
  • A fast-moving, mission-driven culture where smart people do their best work and actually enjoy doing it

Apply