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Applied Machine Learning Intern Jobs in San Pablo, CA

Crowe LLP

Machine Learning Intern

San Francisco, CA · On-site

$27 - $42/hr

Anomaly detection using deep neural networks Numerical optimization applied to problems in ... To that end, there are three major components with which an intern should expect to engage.

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Director, Applied Machine Learning

San Francisco, CA · On-site

$250 - $350/hr

About the Role As Director of Applied ML, you'll lead the function that sits at the intersection of ... Growth: $2,000 learning stipend, ongoing development * Office: Commuting support, free lunch, and ...

Unlearn

Applied Machine Learning Scientist

San Francisco, CA · On-site

$140K - $165K/yr

About Our Team We come from a variety of backgrounds ranging from machine learning to marketing-but ... Applied ML Scientists lead Unlearn's work to develop state-of-the-art ML approaches for generating ...

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

... applied machine learning engineering; or * A graduate degree (M.S. or Ph.D.) in computer science or a related field-such as artificial intelligence, computational neuroscience, or biomedical ...

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All JobsApplied Machine Learning Intern JobsApplied Machine Learning Intern Jobs in San Pablo, CA

Applied Machine Learning Intern information

See San Pablo, CA salary details

$28.7K

$48K

$99.2K

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

As of Aug 29, 2026, the average yearly pay for applied machine learning intern in San Pablo, CA is $47,989.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,600.00 and $51,800.00 per year, depending on experience, location, and employer.

What is the difference between Applied Machine Learning Intern vs Data Science Intern?

AspectApplied Machine Learning InternData Science Intern
Required SkillsMachine learning algorithms, programming (Python, R), data analysisStatistical analysis, data visualization, programming (Python, R)
Work EnvironmentDeveloping ML models, experimenting with algorithms, deploying modelsData cleaning, analysis, reporting insights
Industry UsageTech companies, AI startups, research labsBusiness analytics, market research, finance

Applied Machine Learning Interns focus on developing and deploying machine learning models, requiring knowledge of algorithms and programming. Data Science Interns typically handle data analysis, visualization, and reporting. While both roles involve data skills, applied ML interns work more on model implementation, whereas data science interns focus on insights and data interpretation.

What cities near San Pablo, CA are hiring for Applied Machine Learning Intern jobs?

Cities near San Pablo, CA with the most Applied Machine Learning Intern job openings:

Applied Machine Learning Intern jobs near you
Infographic showing various Applied Machine Learning Intern job openings in San Pablo, CA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 26% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $47,989 per year, or $23.1 per hour.

Machine Learning Intern

Droyd Robotics

San Francisco, CA • On-site

Internship

Re-posted 8 days ago

Job description

About the team
Droyd builds autonomous robotic systems that automate repetitive manual work in real environments. Our robots operate under tight compute, latency, and reliability constraints, so learning systems must work cleanly on real hardware.
Our AI team builds the models and inference systems that let robotic arms see, reason, and act. This work runs on deployed robots, not demos.
About the role
As a Machine Learning Intern at Droyd, you'll work directly on the learning and inference systems that power our robotic arms. You'll train models, run experiments, and help push research into production.
You'll work closely with AI researchers, software engineers, and hardware teams, and contribute to systems that ship to real robots.
This role is based in San Francisco, CA. We're an in-person company. We build faster that way.
In this role, you'll
  • Work across the ML stack, from training to inference
  • Train and evaluate models that run on low-payload robotic systems
  • Run experiments, analyze results, and document findings
  • Learn how model design, data quality, and hardware constraints affect real-world performance
  • Support deployment and testing of models on robotic hardware
We're looking for candidates who
  • Are current juniors or seniors (or equivalent) studying computer science, machine learning, AI, or a related field
  • Have coursework or hands-on experience training ML models using frameworks like PyTorch or JAX
  • Are willing to balance school and work in a fast-moving environment
  • Are curious about robotics and interested in how learning systems behave in the real world
  • Take ownership, ask good questions, and can carry projects forward with guidance
About Droyd
Droyd builds autonomous robotic systems to automate manual work for enterprises. We design the hardware, collect our own data, and train models that operate under real-world constraints.
If we do this right, robots become dependable tools people rely on every day.
Join us and help build systems that ship.

Apply