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Internship Machine Learning Robotics Jobs in California

Horizon Robotics

Research Scientist

Cupertino, CA · Hybrid

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

Horizon Robotics

Research Scientist

Cupertino, CA · On-site

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

Horizon Robotics

Research Scientist

Cupertino, CA · Hybrid

$150K - $300K/yr

We are looking for someone with expertise in and enthusiasm for machine learning research, especially in Robotics, Embodied AI, Reinforcement learning (RL) , etc. As a Research Scientist in the team ...

Waymo

Perception Machine Learning Engineer

Mountain View, CA · On-site +1

$170K - $216K/yr

MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline * Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV ...

Waymo

Perception Machine Learning Engineer

San Francisco, CA · On-site +1

$170K - $216K/yr

MS or PhD Degree in Machine Learning, Robotics, Computer Science or a similar discipline * Publications at top-tier conferences like CVPR, ICCV, ECCV, ICLR, ICML, ICRA, IROS, RSS, NeurIPS, AAAI, IJCV ...

Skild AI

Machine Learning Engineer

San Mateo, CA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA

$160K - $190K/yr

Machine Learning Engineer Machina Labs is changing the way manufacturing works. We build ... By integrating advanced metal forming, robotics, and automated production inside a flexible factory ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

By integrating advanced metal forming, robotics, and automated production inside a flexible factory ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

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Internship Machine Learning Robotics information

What is the difference between Internship Machine Learning Robotics vs Internship Data Science?

AspectInternship Machine Learning RoboticsInternship Data Science
Required SkillsProgramming (Python, C++), Robotics, Machine LearningStatistics, Programming (Python, R), Data Analysis
Work EnvironmentRobotics labs, manufacturing, research facilitiesData centers, corporate offices, research institutions
Industry UsageRobotics companies, automation, AI hardwareFinance, healthcare, marketing, tech firms

Internship Machine Learning Robotics focuses on developing AI algorithms for robotic systems, combining hardware and software skills. In contrast, Internship Data Science emphasizes analyzing data to extract insights, often in business or research settings. Both internships require programming skills, but their applications and environments differ significantly.

What are the most commonly searched types of Machine Learning Robotics jobs in California? The most popular types of Machine Learning Robotics jobs in California are:
Internship Machine Learning Robotics jobs near you

Machine Learning Engineer - Robot Perception

Maven Robotics

San Francisco, CA • On-site

Other

Posted 20 days ago

Job description

Company Overview

Maven Robotics is building the world's leading general-purpose AI robots.

We are currently operating in stealth and are growing the world's best team in AI robotics. We are looking for self-starters that are the world's best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.

Role Description

We are looking to recruit an exceptional Machine Learning Engineer - Robot Perception to design, implement, test, and deploy robot perception algorithms that power our robots' ability to understand and interact with the world.

In this role you will:

  • Develop, train, and deploy ML-based perception algorithms for object detection, pose estimation, tracking, and scene understanding.
  • Integrate sensor fusion techniques using cameras, depth sensors, IMUs, and tactile feedback.
  • Optimize real-time perception pipelines for low-latency and robust performance in dynamic environments.
  • Work closely with hardware engineers to design sensor configurations and optimize perception models for onboard deployment.
  • Contribute to our broader AI and autonomy stack, ensuring seamless integration with reasoning, manipulation, planning and control.
  • Collaborate across disciplines to ensure seamless integration of ML models and provide technical mentorship to junior engineers.
Qualifications

Must-have:

  • MS or PhD in machine learning, computer science, robotics, or a related field.
  • Strong background in computer vision, deep learning, and sensor fusion.
  • Proficiency in Python and C++, with experience in frameworks like PyTorch, TensorFlow, OpenCV, and ROS.
  • Hands-on experience with real-world robotics perception systems (e.g., SLAM, 3D reconstruction, multimodal perception).
  • Experience working with hardware, including setting up and calibrating cameras, LiDAR, and other sensors.
  • Experience with data collection, preprocessing, and management in the context of training ML models.
  • Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
  • Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:

  • Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
  • Experience in:
    • Developing models that can handle noisy, incomplete, or sparse data.
    • Deployment of ML models to edge devices for real-time inference (e.g., NVIDIA Jetson).
    • Accelerating ML training processes using GPU, TPU, or other HW accelerators.
    • General knowledge of robotics principles, including kinematics, dynamics, and control.

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