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Remote Machine Learning Robotics Jobs in California

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Remote Machine Learning Robotics information

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Robotics Engineer, and why are they important?

To thrive as a Remote Machine Learning Robotics Engineer, you need a solid background in robotics, machine learning algorithms, programming (Python, C++), and typically a degree in computer science, robotics, or a related field. Familiarity with robotics frameworks (like ROS), machine learning libraries (such as TensorFlow or PyTorch), and experience with cloud platforms or remote collaboration tools are highly valued. Strong problem-solving abilities, initiative, and effective remote communication skills help you excel in distributed teams. These competencies enable you to develop intelligent robotic systems efficiently, collaborate across locations, and drive innovation in a rapidly evolving field.

How do remote machine learning robotics professionals typically collaborate with hardware teams when working off-site?

Remote machine learning robotics professionals often collaborate closely with hardware teams through regular virtual meetings, shared documentation, and cloud-based development environments. They use simulation tools to test algorithms before deployment and rely on video calls or live streams to observe hardware tests in real time. Effective communication and detailed feedback are essential to ensure that software and hardware integration runs smoothly, despite working from different locations. This collaborative approach helps address issues quickly and keeps projects on track.

What is a Remote Machine Learning Robotics job?

A Remote Machine Learning Robotics job involves developing and implementing machine learning algorithms to control and improve robotic systems, all while working from a remote location. Professionals in this field use artificial intelligence techniques to enable robots to learn from data and adapt to new tasks. They collaborate with teams virtually, leveraging cloud-based tools and simulation environments to design, test, and deploy robotic solutions. This role typically requires strong programming skills, knowledge of robotics frameworks, and experience with machine learning models.

What is the difference between Remote Machine Learning Robotics vs Remote Data Scientist?

AspectRemote Machine Learning RoboticsRemote Data Scientist
Required CredentialsDegree in Robotics, Computer Science, or related fields; experience with ML algorithms and robotics platformsDegree in Data Science, Statistics, or related fields; proficiency in ML, statistics, and programming
Work EnvironmentHands-on with robotics hardware, simulation environments, and software developmentData analysis, modeling, and visualization primarily on software platforms
Employer & Industry UsageRobotics companies, manufacturing, autonomous vehicles, research labsTech firms, finance, healthcare, research institutions

Remote Machine Learning Robotics focuses on developing intelligent systems that integrate robotics hardware with machine learning algorithms, often requiring hands-on hardware work. In contrast, Remote Data Scientists primarily analyze data and build models using software tools. Both roles involve ML expertise but differ in work environment and industry applications.

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:
What are popular job titles related to Remote Machine Learning Robotics jobs in California? For Remote Machine Learning Robotics jobs in California, the most frequently searched job titles are:
What cities in California are hiring for Remote Machine Learning Robotics jobs? Cities in California with the most Remote Machine Learning Robotics job openings:
Machine Learning Engineer, Depot Automation

Machine Learning Engineer, Depot Automation

Waymo

Mountain View, CA • On-site, Remote

$175K - $215K/yr

Other

Posted 16 days ago


Job description

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver-The World's Most Experienced Driver-to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

This role is at the intersection of robotics and machine learning, driving the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet. You will lead efforts to generalize complex depot operations-such as exterior cleaning, sensor calibration, and maintenance checks-using advanced robotics. Key work involves leveraging foundation models, reinforcement learning, simulation, and integrating ML models in production at scale. You will interface closely with operations teams to translate real-world needs into robust, working solutions.

This role follows a hybrid work schedule and reports to a Director, Hardware and Sensors.

You will:

  • Drive the next generation of operational efficiency for Waymo's rapidly expanding autonomous fleet
  • Contribute to accomplishing complex depot operations using advanced robotics
  • Focus on complex depot operations, such as charging, interior cleaning, vehicle inspection, and routine vehicle maintenance tasks
  • Leverage foundation models, reinforcement learning, and simulation
  • Integrate ML models in production at scale
  • Interface closely with operations teams to translate real-world needs into robust, working solutions

You have:

  • 3+ years of experience in training and evaluating large machine learning models
  • 3+ years of experience with robotics, preferably industrial robotics
  • Expertise in reinforcement learning and its applications to real-world problems

We prefer:

  • A PhD in Machine Learning, Robotics, or a related technical field or equivalent experience
  • Experience with applying machine learning techniques to large-scale industrial problems is a plus
  • Background in collaborating with internal and external research partners on applying ML to large-scale industry scale problems

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range
$175,000—$215,000 USD