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Medical Machine Learning Internship Jobs in California

TEKsystems

Machine Learning Engineer

San Diego, CA · Hybrid

$70 - $95/hr

Production Machine Learning Deployments * Model Monitoring, Observability, and Optimization ... If eligible, the benefits available for this temporary role may include the following: • Medical ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

About the Role At Poesis, machine learning and artificial intelligence open the door to improved ... Benefits We offer excellent medical, dental, and vision coverage, alongside a strong benefits ...

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 ... Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and ...

Intel

Machine Learning Engineer

Folsom, CA

... internship experiences and or schoolwork/classes/research. Benefits at Intel Our total rewards ... Candidates should never be required to pay recruitment fees, medical examination fees, or any other ...

Intel

Machine Learning Engineer

Santa Clara, CA

... internship experiences and or schoolwork/classes/research. Benefits at Intel Our total rewards ... Candidates should never be required to pay recruitment fees, medical examination fees, or any other ...

Hadrian Automation

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ... Medical, dental, vision, and life insurance plans for employees * 401k * Relocation support may be ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$184K - $324K/yr

... Machine Learning Engineer with experience developing ML models for computer vision and graphics ... Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and ...

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 ... Medical history is scattered across systems that don't communicate. Physicians have minutes to ...

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Medical Machine Learning Internship information

What kinds of projects and responsibilities can I expect during a Medical Machine Learning Internship?

As a Medical Machine Learning Intern, you'll typically work on real-world datasets to develop, test, and refine machine learning models aimed at improving healthcare outcomes. Your daily tasks may include data preprocessing, feature engineering, model selection, and performance evaluation under the guidance of experienced data scientists or clinicians. Collaboration is key, as you'll often work with multidisciplinary teams, including software engineers, clinicians, and researchers. This hands-on experience allows you to gain practical skills and contribute to impactful projects that can enhance patient care or medical research.

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

To thrive as a Medical Machine Learning Intern, you need a solid background in statistics, programming (Python or R), and foundational knowledge of machine learning algorithms, typically supported by coursework or a relevant degree in computer science, engineering, or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience working with medical datasets or healthcare IT systems are highly valued. Strong analytical thinking, attention to detail, and effective communication skills will help you collaborate with interdisciplinary teams and present findings clearly. These skills are crucial for developing accurate, impactful models that address real-world healthcare challenges and ensure patient safety.

What is a Medical Machine Learning Internship?

A Medical Machine Learning Internship is a temporary position where students or recent graduates work on projects that apply machine learning techniques to healthcare and medical datasets. Interns typically collaborate with data scientists, clinicians, and researchers to develop algorithms that can assist in diagnosing diseases, predicting patient outcomes, or improving healthcare processes. This role provides hands-on experience with real-world medical data, exposure to regulatory considerations, and the opportunity to contribute to impactful healthcare innovations. Such internships help interns build technical and domain-specific skills, preparing them for future careers in medical data science.
What are popular job titles related to Medical Machine Learning Internship jobs in California? For Medical Machine Learning Internship jobs in California, the most frequently searched job titles are:
What job categories do people searching Medical Machine Learning Internship jobs in California look for? The top searched job categories for Medical Machine Learning Internship jobs in California are:
What cities in California are hiring for Medical Machine Learning Internship jobs? Cities in California with the most Medical Machine Learning Internship job openings:
Medical Machine Learning Internship jobs near you
Infographic showing various Medical Machine Learning Internship job openings in California as of July 2026, with employment types broken down into 7% Internship, 1% As Needed, 70% Full Time, 19% Part Time, 2% Temporary, and 1% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution.
Mid-Level Machine Learning Engineer

Mid-Level Machine Learning Engineer

TetraMem - Accelerate The World

San Jose, CA • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
TetraMem is a company focused on accelerating the world through innovative technology, and they are seeking a Mid-Level Machine Learning Engineer to develop and optimize machine learning models for edge AI applications. The role involves collaborating with hardware and software teams, providing mentorship, and researching state-of-the-art ML techniques to enhance model efficiency.
Responsibilities:
• Develop, optimize, and deploy lightweight machine learning models for edge AI applications, particularly for audio processing.
• Implement and optimize ML models on embedded platforms, including FPGA and custom ASIC solutions.
• Work closely with hardware and software teams to integrate ML models into production systems.
• Research and implement state-of-the-art ML techniques to enhance model efficiency, latency, and power consumption for embedded AI applications.
• Improve inference efficiency and model compression techniques, including quantization, pruning, and knowledge distillation.
• Collaborate with cross-functional teams to drive innovation and contribute to the overall system architecture.
• Provide technical leadership and mentorship to junior engineers.
• Publish research findings, present at conferences, and contribute to open-source projects when applicable.
Qualifications:
Required:
• 5+ years of experience or PhD in Computer Science, Electrical Engineering, or related fields.
• Strong experience in machine learning, with a focus on edge AI and lightweight model deployment.
• Expertise in ML frameworks such as PyTorch, TensorFlow, JAX.
• Proficiency in programming languages such as C/C++, Python, and experience with ML model optimization.
• Ability to work independently and collaboratively in a fast-paced startup environment.
• Ability to provide mentorship, technical guidance, and career development support to junior engineers and interns.
Preferred:
• Understanding of ML compiler and runtime design.
• Experience working with tools such as Optimum, ONNX, TensorRT, TFLite/LiteRT, ncnn, or CoreML.
• Familiarity with hardware acceleration techniques.
• Experience in embedded system development.
Company:
TetraMem is developing cutting-edge analog computing solutions for AI applications, offering exceptional performance with ultra-low power consumption. Founded in 2018, the company is headquartered in Newark, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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