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Machine Learning Engineer Intern Jobs in San Ramon, CA

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 ...

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...

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 ...

Staff Machine Learning Engineer Overview: As a Staff Machine Learning Engineer, you will be the overall tech lead of a single AI/Machine Learning team, responsible for the tech design and tech health ...

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 ...

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 ...

... machine learning/deep learning systems, computer vision, graphics, computational imaging applications.Experience with Pytorch. MS/PhD in computer vision, electrical, optical or computer engineering ...

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of data-driven and ML-powered solutions for semiconductor R&D, test, and operations teams. In this role ...

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 ...

... engineers across Apple.","responsibilities":"Design, train and tune machine learning algorithms, support camera architects to drive innovative solutions for imaging and sensing challenges, and ...

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 ...

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Machine Learning Engineer Intern information

See San Ramon, CA salary details

$28.5K

$47.6K

$98.3K

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

As of May 30, 2026, the average yearly pay for machine learning engineer intern in San Ramon, CA is $47,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,300.00 and $51,400.00 per year, depending on experience, location, and employer.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

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

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.
What are the most commonly searched types of Machine Learning Engineer jobs in San Ramon, CA? The most popular types of Machine Learning Engineer jobs in San Ramon, CA are:
What job categories do people searching Machine Learning Engineer Intern jobs in San Ramon, CA look for? The top searched job categories for Machine Learning Engineer Intern jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Machine Learning Engineer Intern jobs? Cities near San Ramon, CA with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in San Ramon, CA as of May 2026, with employment types broken down into 92% Full Time, 7% Part Time, and 1% Contract. Highlights an 68% Physical, 1% Hybrid, and 31% Remote job distribution, with an average salary of $47,588 per year, or $22.9 per hour.

Machine Learning Engineer

Latent

San Francisco, CA • On-site

$225K - $300K/yr

Full-time

Posted 25 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.