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Remote Machine Learning Robotics Jobs in California

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Remote Machine Learning Robotics information

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 are the key skills and qualifications needed to thrive as a remote machine learning robotics engineer?

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 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 job categories do people searching Remote Machine Learning Robotics jobs in California look for?

The top searched job categories for Remote Machine Learning Robotics jobs in California 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:

Senior Machine Learning Engineer - AV Labs

Uber Technologies, Inc.

Sunnyvale, CA • On-site, Remote

Full-time

Retirement

Re-posted 5 days ago


Uber rating

6.7

Company rating: 6.7 out of 10

Based on 116 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire


Job description

About the Role

Uber is launching AV Labs to accelerate the autonomous technology ecosystem. We're building out a high-velocity team of multi-disciplinary experts to turn real-world operations into high-quality data for our autonomous partners. This team is focused on the hardest problem in AV today: unlocking real-world, long-tail driving data. Autonomy is now a data race-and Uber has an edge: We collect rare, real-world driving data at a scale and capital efficiency no one else can match.

As a Senior ML Engineer, you will be at the forefront of Physical AI, building advanced autonomy algorithms and models to add rich semantics to our massive driving data. You will be responsible for the development and implementation of the latest machine learning techniques that enables better data mining, deep scene understanding, and causal modeling of ego vehicle behavior. The ideal candidate will be able to identify complex edge cases, provide robust algorithmic solutions, and set a high technical excellence bar.

What the Candidate Will Do
  • Algorithm Development: Lead the development of autonomy algorithms and foundation models that extract high-fidelity semantic meaning from complex urban edge cases to enrich our L4 data lake.
  • Systems Architecture Design: Architect scalable ML systems, including management of upstream sensor dependencies.
  • Technical Leadership: Partner with fellow engineers to architect, design, and build scalable solutions for ML technology that can stand the test of scale and availability.
  • Dataset Optimization: Deliver high-quality datasets to accelerate ML technologies through advanced sensor data collection, processing, and auto-labeling.
  • Cross-Functional Collaboration: Partner with platform, product, and security engineering teams to enable the successful deployment of the latest machine learning techniques into production.
Basic Qualifications
  • 4+ years of working experience in the ML/Robotics industry.
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields.
  • Proficient in Python and Linux environments.
  • Familiar with modern AI/ML frameworks (e.g., PyTorch).
Preferred Qualifications
  • Experience in the Autonomous Driving domain.
  • Proven track record of deploying ML models in safety-critical physical systems.
  • Master's or PhD degree in Computer Vision, Robotics, or Machine Learning.
  • Familiarity with C++ and high-performance computing.
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Ready to Ride?


This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.


You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.


Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.


Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.


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