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Hourly Machine Learning Intern information

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

AspectHourly Machine Learning InternHourly Data Science Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually enrolled in or graduated from a program in Data Science, Statistics, or related areas; proficiency in data analysis tools
Work EnvironmentTech companies, startups, research labs focusing on ML model developmentOrganizations applying data analysis to business problems, often in tech, finance, or healthcare sectors
Employer & Industry UsageCommonly used in AI/ML-focused roles within tech industriesWidely used across industries for data-driven decision making

The Hourly Machine Learning Intern focuses on developing and testing machine learning models, requiring programming and ML-specific skills. In contrast, the Hourly Data Science Intern emphasizes analyzing data to extract insights, often involving statistical analysis and data visualization. Both roles are valuable entry points in data-related fields but differ in technical focus and daily tasks.

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The most popular types of Machine Learning Intern jobs in California are:

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Hourly Machine Learning Intern jobs near you

Machine Learning Intern

Droyd Robotics

San Francisco, CA • On-site

Internship

Re-posted 25 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