Strong understanding of RL fundamentals (e.g., policy optimization, value methods, model-based RL ... Solid software engineering skills and ability to build scalable, reliable systems * Ability to ...
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Sacramento, CA · On-site
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Manufacturing Engineers
Sacramento, CA · On-site
$77K - $100K/yr
... Electrical Methods Engineer) · Hands on experience on Creo, Windchill (expert level), Team centre, SAP Desired Knowledge / Experience · 5-8 years experience in Manufacturing background with ...
The Reserve Engineer (RE) is someone who is knowledgeable with computer hardware and provides our clients with top-notch customer service. The RE serves as Cobalt's "boots on the ground" and are part ...
Quick apply
The Reserve Engineer (RE) is someone who is knowledgeable with computer hardware and provides our clients with top-notch customer service. The RE serves as Cobalt's "boots on the ground" and are part ...
AI Inference Engineer Location: San Jose, CA Contract / C2H Duration: 6-12Months About the Role We are seeking a highly skilled AI Inference Engineer to join our team and drive the performance ...
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Methods Engineer information
See California salary details
$37.5K - $51.3K
5% of jobs
$51.3K - $65K
7% of jobs
$65K - $78.8K
9% of jobs
$81.7K is the 25th percentile. Wages below this are outliers.
$78.8K - $92.6K
14% of jobs
The median wage is $105K / yr.
$92.6K - $106.4K
16% of jobs
$106.4K - $120.1K
13% of jobs
$120.1K - $133.9K
6% of jobs
$141.2K is the 75th percentile. Wages above this are outliers.
$133.9K - $147.7K
8% of jobs
$147.7K - $161.4K
8% of jobs
$161.4K - $175.2K
7% of jobs
$175.2K - $189K
5% of jobs
$37.5K
$114.3K
$189K
How much do methods engineer jobs pay per year?
What are the key skills and qualifications needed to thrive as a Methods Engineer, and why are they important?
What is the difference between Methods Engineer vs Process Engineer?
| Aspect | Methods Engineer | Process Engineer |
|---|---|---|
| Required Credentials | Bachelor's in Engineering, certifications in process improvement or manufacturing | Bachelor's in Engineering, chemical or industrial engineering preferred |
| Work Environment | Manufacturing plants, production lines, industrial settings | Manufacturing facilities, chemical plants, or industrial environments |
| Employer & Industry Usage | Manufacturing, automotive, aerospace, industrial sectors | Chemical, manufacturing, energy, and industrial sectors |
| Common Search & Comparison | Methods Engineer vs Process Engineer |
Methods Engineers focus on developing and optimizing manufacturing processes, emphasizing efficiency and quality improvements. Process Engineers also work on process design and optimization but often have a broader scope, including chemical processes and system integration. Both roles require similar technical credentials and are found in manufacturing and industrial settings, but Methods Engineers typically specialize in specific methods and procedures within production environments.
What does a Methods Engineer do?
How does a Methods Engineer typically interact with production and quality teams on a daily basis?
What engineers make $500,000?
What engineers make $300,000 a year?
What job makes $10,000 a month without a degree?

Job description
Our Helix team is responsible for developing the core AI systems that power humanoid autonomy. We are looking for a Helix AI Engineer, Reinforcement Learning to develop learning systems that enable robots to acquire skills through interaction, feedback, and experience.
This role focuses on applying and advancing reinforcement learning across simulation and real-world environments-improving policy performance, robustness, and long-horizon decision-making in embodied systems.
Responsibilities
- Design and implement reinforcement learning algorithms for embodied agents operating in real-world and simulated environments
- Train policies that learn from interaction, feedback, and large-scale experience across diverse tasks
- Develop reward modeling, credit assignment, and exploration strategies for complex, long-horizon behaviors
- Improve policy robustness to real-world challenges such as noise, partial observability, and environment variability
- Work across online and offline RL settings, including learning from large-scale logged robot data
- Collaborate closely with pretraining, video, generative, agent, and robot learning teams to integrate RL into the full autonomy stack
- Build scalable training systems for RL, including distributed rollouts, simulation infrastructure, and experiment management
- Design evaluation frameworks to measure policy performance, stability, and generalization
- Experience developing and applying reinforcement learning algorithms in complex environments
- Strong understanding of RL fundamentals (e.g., policy optimization, value methods, model-based RL)
- Experience training policies in simulation and/or real-world systems
- Proficiency in Python and deep learning frameworks such as PyTorch
- Experience with large-scale experimentation and distributed training systems
- Strong experimental rigor and ability to diagnose and improve learning systems
- Solid software engineering skills and ability to build scalable, reliable systems
- Ability to operate independently and drive ambiguous, high-impact technical problems
- Experience applying RL to robotics, control systems, or embodied AI
- Experience with large-scale RL infrastructure (distributed rollouts, simulation at scale)
- Background in offline RL, imitation learning, or hybrid learning approaches
- Experience with reward modeling or human-in-the-loop learning
- Experience at leading AI labs such as OpenAI, Google DeepMind, Anthropic, or xAI
- Familiarity with robotics systems, simulation environments, or real-world deployment constraints
- Publication record in reinforcement learning, machine learning, or robotics
The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.