ZipRecruiter

Log In

1

Machine Learning Engineer Jobs in Fremont, CA (NOW HIRING)

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 groups: those with wealth and access, and those with physicians in their immediate family. For ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product ...

Apple

Machine Learning Engineer (Search)

Cupertino, CA · On-site

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

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 ...

Adobe

Machine Learning Engineer

San Jose, CA · On-site

As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...

Docusign

Machine Learning Engineer

San Francisco, CA · On-site

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$184K - $324K/yr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Apple

Machine Learning Engineer

Cupertino, CA

$216K - $324K/yr

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$150K - $277K/yr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Fremont, CA

Machine Learning Engineer information

See Fremont, CA salary details

$34.5K

$141K

$211.8K

How much do machine learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning engineer in Fremont, CA is $140,959.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,100.00 and $169,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Fremont, CA? The most popular types of Machine Learning Engineer jobs in Fremont, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Fremont, CA? For Machine Learning Engineer jobs in Fremont, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Fremont, CA look for? The top searched job categories for Machine Learning Engineer jobs in Fremont, CA are:
What cities near Fremont, CA are hiring for Machine Learning Engineer jobs? Cities near Fremont, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Fremont, CA as of July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $140,959 per year, or $67.8 per hour.

Machine Learning Engineer

Latent

San Francisco, CA • On-site

$225K - $300K/yr

Full-time

Re-posted 10 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