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Junior Machine Learning Engineer Jobs in San Ramon, 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 groups: those with wealth and access, and those with physicians in their immediate family. For ...

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

$100K - $300K/yr

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

  • Medical

  • Retirement

  • PTO

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 ...

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

Provide guidance and mentorship to junior engineers, fostering a culture of learning and growth ... Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch)

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking Machine Learning Engineers to build their platform for training, evaluating, and deploying interpretable AI systems at scale, contributing to the development of key technologies and ...

Goodfire

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will play a central role in building the core technology for training, evaluating, and deploying interpretable frontier AI systems, contributing to tools, infrastructure ...

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 ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

  • Medical

  • Retirement

  • PTO

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 ...

Eve

Machine Learning Engineer

San Francisco, CA

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

Apex Systems

Machine Learning Engineer

Pleasanton, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Position starts off as a 6 month contract Machine Learning Engineer Location: Pleasanton, California (Remote) Role Overview This role is focused on developing, deploying, and optimizing machine ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$150K - $277K/yr

  • Medical

  • Dental

  • Retirement

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 ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$184K - $324K/yr

  • Medical

  • Dental

  • Retirement

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 ...

Stackruit Ltd.

Machine Learning

San Francisco, CA · On-site

$200 - $250/hr

First Machine Learning Engineer (US Remote - $200k-$250k) Do you dream of using machine learning to empower businesses to take action on their data? Join a mission-driven company! About Us * We're ...

New

Quantcast

Machine Learning Engineer

San Francisco, CA · On-site

$151.30 - $178/hr

As a Machine Learning Engineer you care about the health and maintainability of our systems and the velocity of the engineering teams. You explore data, research new algorithms, experiment with proof ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

$90 - $130/hr

We are seeking machine learning engineers to join our team full-time. As part of your role, you will help us build pipelines of data collection, data extraction, data filtering/synthetic data ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

  • Medical

  • Retirement

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 ...

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 ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in San Ramon, CA

Junior Machine Learning Engineer information

See San Ramon, CA salary details

$37.4K

$80.2K

$122.4K

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

As of Aug 20, 2026, the average yearly pay for junior machine learning engineer in San Ramon, CA is $80,237.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,200.00 and $89,400.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
More about Junior Machine Learning Engineer jobs

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For Junior Machine Learning Engineer jobs in San Ramon, CA, the most frequently searched job titles are:

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Cities near San Ramon, CA with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in San Ramon, CA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 20% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $80,237 per year, or $38.6 per hour.

Machine Learning Engineer

Latent

San Francisco, CA • On-site

$225K - $300K/yr

Full-time

Re-posted 16 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