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Senior Machine Learning Engineer Jobs in Fairfield, CA

Latent

Machine Learning Engineer

San Francisco, CA · On-site

$225K - $300K/yr

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two ... We are primarily hiring for senior and staff-level engineers who are comfortable owning critical ...

Career Renew

Senior ML Engineer

San Francisco, CA · Remote

$180K - $240K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 180-240K USD plus benefits plus equity.

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Fairfield, CA

Senior Machine Learning Engineer information

See Fairfield, CA salary details

$60.6K

$128.8K

$186.7K

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

As of Aug 6, 2026, the average yearly pay for senior machine learning engineer in Fairfield, CA is $128,796.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $146,000.00 per year, depending on experience, location, and employer.

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 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 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 popular job titles related to Senior Machine Learning Engineer jobs in Fairfield, CA? For Senior Machine Learning Engineer jobs in Fairfield, CA, the most frequently searched job titles are:
What cities near Fairfield, CA are hiring for Senior Machine Learning Engineer jobs? Cities near Fairfield, CA with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Fairfield, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,796 per year, or $61.9 per hour.

Machine Learning Engineer

Latent

San Francisco, CA • On-site

$225K - $300K/yr

Full-time

Re-posted 3 days ago

Job description

Machine Learning Engineer
About Latent Health
Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family.
For everyone else, care is fragmented and impersonal.
Medical history is scattered across systems that don't communicate. Physicians have minutes to understand decades of context. And when something goes wrong, patients are left with tools that understand medicine broadly-but not the individual.
We believe this can be fundamentally rebuilt.
At Latent Health, we are building systems that understand both:
  • the population (clinical knowledge at scale)
  • and the individual (longitudinal patient history)

Our models are designed to answer complex clinical questions with patient-specific context and verifiable reasoning.
Our dataset represents one of the most clinically diverse populations in the United States, including patients with chronic illness and complex disease. Each patient record contains extraordinary depth.
ML at Latent Health
The Machine Learning team is responsible for building systems that run in real clinical workflows.
We work on:
  • Verifiable reinforcement learning at scale
  • Mid-training and post-training of foundation models
  • Novel objectives derived from longitudinal patient data

We are a small group of researchers and engineers focused on pushing the frontier while shipping real systems into production.
We are a small team and expect engineers to take ownership of critical systems, not components.
The Role
As a Machine Learning Engineer, you will own the design, development, and operation of production-grade ML systems that run in real clinical workflows.
You will drive systems from ambiguous problem definition through to reliable production deployment, setting technical direction along the way.
We are primarily hiring for senior and staff-level engineers who are comfortable owning critical systems end-to-end.
This role involves owning systems that directly impact real patient outcomes.
What You'll Do
  • Own end-to-end ML systems, including architecture, data, modeling, evaluation, and production infrastructure
  • Train and fine-tune large language models (LLMs) for:
    • Clinical reasoning
    • Medical question answering
    • Evidence-grounded generation
  • Make and own tradeoffs across accuracy, latency, cost, and safety in high-stakes production environments
  • Develop evaluation frameworks to ensure model safety and clinical validity
  • Integrate ML systems into product workflows and patient-facing applications
  • Monitor system performance in production and iterate based on real-world usage and feedback
  • Define what "correct" means in ambiguous clinical workflows in collaboration with engineers and clinicians

What We're Looking For
  • Strong foundation in machine learning and software engineering
  • Track record of building and owning ML systems in production where performance, reliability, or correctness materially mattered
  • Experience driving ambiguous ML problems from 0→1, including problem formulation, model design, and productionization
  • Hands-on experience with PyTorch or similar frameworks
  • Ability to operate independently in high-ambiguity environments with minimal guidance
  • Strong product and engineering judgment - you know when to use ML, when not to, and how to scope problems accordingly
  • Comfort working in a fast-moving, early-stage environment
  • Experience working on systems where decisions have real-world consequences (e.g., healthcare, finance, infrastructure)

Nice to Have
  • Experience deploying LLMs in production environments
  • Experience building distributed systems or large-scale data pipelines
  • Experience working with clinical, biomedical, or other regulated datasets

Why Join Latent Health
  • Work on high-stakes problems with real impact on patient care
  • Build systems that define how AI is trusted in clinical decision-making
  • Significant ownership in a small, high-caliber team
  • Competitive compensation and meaningful equity

Location
We are based in San Francisco and work together in person.
We spend most of the week in the office and prioritize candidates who are excited to work this way.
Compensation
  • Base salary: $225,000 - $300,000+
  • Meaningful equity in an early-stage, Series A company

Closing
If you're interested in building systems that bring truly personalized healthcare to millions of patients, we'd love to talk.

Apply