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Machine Learning Research Intern Jobs in Mountain View, CA

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

... research practical ML algorithms and build with us the next generation of video technology. We are ... frontier of machine learning - including computer vision, image and video generation ...

Meta is seeking a Research Scientist to join our Core Machine Learning Research team, where we advance the foundational AI and ML technologies that power Meta's family of products at scale. In this ...

Research, develop, implement, and evaluate new machine learning and data analysis techniques for multiple applications in a collaborative scientific environment. * Actively participate with project ...

Research, develop, implement, and evaluate new machine learning and data analysis techniques for multiple applications in a collaborative scientific environment. * Actively participate with project ...

Research, develop, implement, and evaluate new machine learning and data analysis techniques for multiple applications in a collaborative scientific environment. * Actively participate with project ...

Showing results 21-40

Machine Learning Research Intern information

See Mountain View, CA salary details

$30.1K

$50.2K

$103.8K

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

As of Sep 5, 2026, the average yearly pay for machine learning research intern in Mountain View, CA is $50,235.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,300.00 and $54,300.00 per year, depending on experience, location, and employer.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.

What are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What are popular job titles related to Machine Learning Research Intern jobs in Mountain View, CA?

For Machine Learning Research Intern jobs in Mountain View, CA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Research Intern jobs in Mountain View, CA look for?

The top searched job categories for Machine Learning Research Intern jobs in Mountain View, CA are:

What cities near Mountain View, CA are hiring for Machine Learning Research Intern jobs?

Cities near Mountain View, CA with the most Machine Learning Research Intern job openings:

Infographic showing various Machine Learning Research Intern job openings in Mountain View, CA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 26% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $50,235 per year, or $24.2 per hour.

Machine Learning Engineer

Advatix Inc.

San Mateo, CA • On-site

$110 - $165/hr

Other

Medical, Dental, Vision, PTO

Re-posted yesterday


Key responsibilities

  • Design, train, and optimize custom deep learning models that understand CAD workflows and generate intelligent next‑step design recommendations

  • Build and maintain scalable Python‑based training, evaluation, and experimentation pipelines, and transform CAD and geometry data into high‑quality training datasets

  • Own the complete ML lifecycle from research and prototyping through deployment, monitoring, and optimization, including architecting model‑serving infrastructure


Job description

Department: Information Technology, Type: Full Time

Job Title: Machine Learning Engineer / Research Engineer

Pay: $$110,000 – $165,000 Base Salary + Equity

Shift: N/A

Location: San Mateo, CA (Peninsula) – Onsite Preferred

Schedule: Full time, Permanent Role

Visa Sponsorship: Not Available

Relocation Assistance: Not Available

Role Summary

We are looking for a highly skilled Machine Learning Engineer / Research Engineer to join our founding team and help develop intelligent systems that transform how hardware and mechanical engineers design products. This is a unique opportunity to work at the intersection of cutting‑edge machine learning research and real‑world engineering applications. You'll collaborate directly with founders, engineers, and customers to design, train, deploy, and continuously improve machine learning systems that accelerate CAD workflows and hardware design. As one of the earliest ML hires, you will have significant ownership over technical direction, architecture decisions, and the long‑term evolution of our AI platform.

Key Responsibilities Machine Learning Research & Development
  • Design, train, and optimize custom deep learning models that understand CAD workflows and generate intelligent next‑step design recommendations.
  • Develop novel machine learning approaches for geometry, design, and engineering‑related datasets.
  • Evaluate emerging research in areas such as sequence modeling, geometric deep learning, representation learning, and foundation models.
Data & Model Infrastructure
  • Build and maintain scalable Python‑based training, evaluation, and experimentation pipelines.
  • Transform complex, real‑world CAD and geometry data into high‑quality training datasets and signals.
  • Implement robust offline and online evaluation frameworks to measure model performance and business impact.
Production ML Systems
  • Own the complete ML lifecycle from research and prototyping through deployment, monitoring, and optimization.
  • Architect model‑serving infrastructure and backend components that enable fast, reliable integration into CAD environments.
  • Establish best practices for experimentation, logging, model versioning, and performance monitoring.
Cross‑Functional Collaboration
  • Work closely with founders, mechanical engineers, hardware engineers, and early customers to understand workflows and translate them into ML solutions.
  • Collaborate with backend engineers on APIs, infrastructure, data models, and platform scalability.
  • Help define the long‑term strategy for applying machine learning to hardware and CAD design.
Skills & Qualifications Machine Learning Expertise
  • 4+ years of hands‑on machine learning experience in industry, research, or a combination of both.
  • Equivalent Master's or PhD research experience will be considered.
  • Demonstrated success designing, training, improving, and deploying machine learning models—not simply utilizing hosted AI APIs.
Deep Learning & Research
  • Expert‑level proficiency with PyTorch (preferred) or similar frameworks such as TensorFlow or JAX.
  • Experience implementing custom architectures, loss functions, optimization methods, and training loops.
  • Strong understanding of model evaluation, experimentation, and performance trade‑offs.
Software Engineering
  • Strong Python programming skills with experience building production‑ready systems.
  • Ability to write clean, maintainable, and well‑tested code with appropriate documentation and abstractions.
  • Experience developing scalable ML infrastructure and backend services.
Ownership & Execution
  • Proven ability to independently drive projects from concept through deployment.
  • Experience building end‑to‑end ML systems including data pipelines, experimentation frameworks, model training, deployment, and monitoring.
  • Comfortable solving ambiguous, open‑ended technical problems.
Communication & Collaboration
  • Excellent communication skills with the ability to explain technical concepts to both technical and non‑technical stakeholders.
  • Experience working cross‑functionally with engineers, product teams, researchers, and customers.
Startup Mindset
  • Thrives in fast‑paced, high‑ownership environments.
  • Comfortable wearing multiple hats across machine learning, research, backend engineering, and infrastructure.
Preferred Qualifications
  • Published research papers or meaningful open‑source contributions demonstrating novel technical work.
  • Experience with:
    • CAD systems and workflows
    • Computational geometry
    • Computer graphics
    • 3D representations
    • Robotics
    • Familiarity with cloud ML infrastructure (AWS, GCP).
    • Experience with backend frameworks such as FastAPI, Flask, or Django.
Must‑Have Requirements
  • Must be based in the United States and possess valid work authorization.
  • Strong proficiency in Python and modern deep learning frameworks (PyTorch preferred).
  • Demonstrated experience building and deploying custom machine learning models from scratch.
  • Experience designing architectures, creating training pipelines, and shipping ML features to production.
  • Minimum 4 years of relevant industry or equivalent academic experience.
Benefits & Perks
  • Competitive salary ($110,000 – $175,000)
  • Meaningful equity ownership
  • Comprehensive medical, dental, and vision insurance
  • Catered team lunches at the San Mateo office
  • Unlimited/flexible paid time off
  • High‑impact role within a YC‑backed startup
  • Direct collaboration with experienced founders and engineers
  • Significant opportunities for growth, learning, and career advancement
  • Opportunity to help define the future of AI‑powered CAD and hardware design

HRforGrowthis an extension of the Growth Catalyst Group (GCG), a partnership of companies with more than 65 years of operating experience and a history of successfully serving customers across industries and disciplines.

GCG® is one of the world’s leading providers of business transformation solutions related to supply chain and technology solutions for order fulfillment and marketing execution. We are committed to an inclusive workplace that does not discriminate against race, nationality, religion, age, marital status, physical or mental disability, sexual orientation, gender, orgender identity. We believe in diversity and encourage anyqualifiedindividual to apply. We are an EEOCEmployer.

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