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Entry Level Machine Learning Robotics Jobs in California

SoloPoint Solutions

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Robotics Software Engineer

Milpitas, CA · On-site

$90 - $100/hr

Machine Learning experience * Experience with Robot Path Planning * Experience with Software QA * Experience with Kuka, Omron, Fanuc and Universal Robots * Experience with implementing AI and ...

Skild AI

Robotics Engineer, Manipulation

San Mateo, CA · On-site

$100K - $300K/yr

We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with ...

General Atomics

Machine Learning Engineer II

Poway, CA · On-site

$98K - $171K/yr

Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience. * Interface with ...

Alutiiq

Robotics Engineer

San Diego, CA

Specifying requirements for system autonomy, Artificial Intelligence (AI) integration, and machine learning models. Designing and fabricating test environments for unmanned systems and robotics.

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Entry Level Machine Learning Robotics information

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

AspectEntry Level Machine Learning RoboticsEntry Level Data Scientist
Required CredentialsBachelor's in CS, Robotics, or related; knowledge of ML, programmingBachelor's in CS, Statistics, or related; strong analytical skills
Work EnvironmentRobotics labs, manufacturing, research facilitiesCorporate offices, research firms, tech companies
Industry UsageManufacturing, automation, robotics developmentFinance, healthcare, tech, marketing
Common Search/ComparisonYesYes

Entry Level Machine Learning Robotics focuses on developing and programming robotic systems using machine learning techniques, often in manufacturing or research settings. Entry Level Data Scientist emphasizes analyzing data to inform business decisions across various industries. While both roles require programming and analytical skills, their work environments and applications 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:
What are popular job titles related to Entry Level Machine Learning Robotics jobs in California? For Entry Level Machine Learning Robotics jobs in California, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Robotics jobs in California look for? The top searched job categories for Entry Level Machine Learning Robotics jobs in California are:
Entry Level Machine Learning Robotics jobs near you
Infographic showing various Entry Level Machine Learning Robotics job openings in California as of July 2026, with employment types broken down into 1% Locum Tenens, 85% Full Time, 12% Part Time, 1% Temporary, and 1% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution.

Senior Staff Research Engineer - Reinforcement Learning for AI Agents

XPENG

Santa Clara, CA • On-site

$122K - $168K/yr

Other

Posted 20 days ago

Job description

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.
 
We are looking for exceptional Research Engineers / Scientists to design learning systems that allow agents to plan over long horizons, learn effective strategies, and improve through experience.
This role sits at the intersection of reinforcement learning, large language models, and real-world autonomous systems. Autonomous systems must operate reliably in complex, dynamic environments. We believe the next generation of autonomy will involve learning agents that continuously improve through interaction, feedback, and large-scale data. You will help build the learning systems that power these agents.
 
Key Responsibilities:
  • Reinforcement learning methods for LLM-driven agents and decision systems.
  • Policy optimization for long-horizon reasoning and planning.
  • Learning from human or AI feedback (RLHF / RLAIF).
  • Agent training pipelines built on top of our agent infrastructure platform.
  • Evaluation and benchmarking systems for agent capabilities.
  • Learning loops that integrate real-world and simulation data.
  • Contribute to AI systems that continuously improve after deployment.
Basic Qualifications
  • MS or PhD in Computer Science, AI, Machine Learning, Robotics, or a related field.
  • Strong background in reinforcement learning or machine learning.
  • Experience implementing RL algorithms such as PPO, Actor-Critic, or policy gradient methods.
  • Strong programming skills in Python with PyTorch or JAX.
  • Experience building ML training systems or infrastructure.
Preferred Qualifications
  • Experience with RLHF or preference learning.
  • Experience with LLM agents or tool-using AI systems.
  • Multi-agent systems or long-horizon planning.
  • Simulation environments for RL.
  • Publications in NeurIPS, ICML, ICLR, ACL, or related venues.
 
What do we provide:
  • A fun, supportive and engaging environment.
  • Opportunity to make significant impact on transportation revolution by the means of advancing autonomous driving.
  • Opportunity to work on cutting edge technologies with the top talent in the field.
  • Competitive compensation package.
  • Snacks, lunches and fun activities.
 
The base salary range for this full-time position is $244,140 - $413,160, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
 
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.

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