... RL policies before deploying on hardware. • Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams. • Deploy, debug, and ...
... RL policies before deploying on hardware. • Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams. • Deploy, debug, and ...
Research Scientist, Reinforcement Learning - Atlas
Waltham, MA · On-site
$175K - $230K/yr
... RL policies before deploying on hardware. * Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams. * Deploy, debug, and ...
Research Scientist, Reinforcement Learning - Atlas
Waltham, MA · On-site
$175K - $230K/yr
... RL policies before deploying on hardware. * Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams. * Deploy, debug, and ...
Senior Autonomy Controls Engineer - Learning-Based Control
Palo Alto, CA · On-site
$114K - $150K/yr
Work closely with the Principal Controls Engineer to translate classical control insights into ... Model-based RL, residual learning, or hybrid MPC architectures * Control under uncertainty and ...
Senior Autonomy Controls Engineer - Learning-Based Control
Palo Alto, CA · On-site
$114K - $150K/yr
Work closely with the Principal Controls Engineer to translate classical control insights into ... Model-based RL, residual learning, or hybrid MPC architectures * Control under uncertainty and ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
Senior Autonomy Controls Engineer - Learning-Based Control
Palo Alto, CA · Hybrid
$114K - $150K/yr
Work closely with the Principal Controls Engineer to translate classical control insights into ... Model-based RL, residual learning, or hybrid MPC architectures * Control under uncertainty and ...
Senior Autonomy Controls Engineer - Learning-Based Control
Palo Alto, CA · Hybrid
$114K - $150K/yr
Work closely with the Principal Controls Engineer to translate classical control insights into ... Model-based RL, residual learning, or hybrid MPC architectures * Control under uncertainty and ...
Research Scientist, Reinforcement Learning - Atlas
$175K - $230K/yr
... RL policies before deploying on hardware. * Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams. * Deploy, debug, and ...
Research Scientist, Reinforcement Learning - Atlas
$175K - $230K/yr
... RL policies before deploying on hardware. * Integrate learned policies with Atlas's control and software stack through close collaboration with controls and platform teams. * Deploy, debug, and ...
The Research Scientist in AI Controls and Monitoring will design methods and systems to ensure AI ... RL techniques such as RLHF, DPO, GRPO, and similar approaches. Company : Scale's mission is to ...
The Research Scientist in AI Controls and Monitoring will design methods and systems to ensure AI ... RL techniques such as RLHF, DPO, GRPO, and similar approaches. Company : Scale's mission is to ...
Sr. Software Engineer - Real-Time Controls
Austin, TX · On-site
$121K - $160K/yr
Integrate learned policies (RL locomotion / motion imitation) into the real-time controls stack * Perform root-cause analysis for complex hardware-software integration issues * Develop API for ...
Sr. Software Engineer - Real-Time Controls
Austin, TX · On-site
$121K - $160K/yr
Integrate learned policies (RL locomotion / motion imitation) into the real-time controls stack * Perform root-cause analysis for complex hardware-software integration issues * Develop API for ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
... RL-0011 Plutonium Finishing Plant project) in the following areas: * Provide project controls support with preparation, review, and issuance of capital asset project documentation and reports ...
... RL-0011 Plutonium Finishing Plant project) in the following areas: * Provide project controls support with preparation, review, and issuance of capital asset project documentation and reports ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... based RL, and sim-to-real transfer techniques. • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... based RL, and sim-to-real transfer techniques. • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... based RL, and sim-to-real transfer techniques. • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... based RL, and sim-to-real transfer techniques. • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... based RL, and sim-to-real transfer techniques. • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... based RL, and sim-to-real transfer techniques. • A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based ...
Also draft report for OCC to be submitted to DOE Headquarters General Counsel, and an annual Summary Management Review of the management controls for RL in accordance with General Counsel guidelines.
Also draft report for OCC to be submitted to DOE Headquarters General Counsel, and an annual Summary Management Review of the management controls for RL in accordance with General Counsel guidelines.
Machine Learning Engineer
San Francisco, CA · On-site
$134K - $162K/yr
Design, implement, and optimize scalable Simulation and RL infrastructure for training surgical ... Mandatory Notices U.S. Export Controls Disclaimer: In accordance with the U.S. Export ...
Machine Learning Engineer
San Francisco, CA · On-site
$134K - $162K/yr
Design, implement, and optimize scalable Simulation and RL infrastructure for training surgical ... Mandatory Notices U.S. Export Controls Disclaimer: In accordance with the U.S. Export ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
Reinforcement Learning Engineer - Whole Body Control
San Jose, CA · On-site
$200K - $350K/yr
Familiarity with common RL techniques such as: domain randomization, curriculum learning, reward shaping, etc. * Capable of leading complex controls projects and mentoring junior engineers Bonus ...
Reinforcement Learning Engineer - Whole Body Control
San Jose, CA · On-site
$200K - $350K/yr
Familiarity with common RL techniques such as: domain randomization, curriculum learning, reward shaping, etc. * Capable of leading complex controls projects and mentoring junior engineers Bonus ...
Reinforcement Learning Engineer - Whole Body Control
San Jose, CA · Hybrid
$200K - $350K/yr
Familiarity with common RL techniques such as: domain randomization, curriculum learning, reward shaping, etc. * Capable of leading complex controls projects and mentoring junior engineers Bonus ...
Reinforcement Learning Engineer - Whole Body Control
San Jose, CA · Hybrid
$200K - $350K/yr
Familiarity with common RL techniques such as: domain randomization, curriculum learning, reward shaping, etc. * Capable of leading complex controls projects and mentoring junior engineers Bonus ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
Senior Reinforcement Learning Engineer
Austin, TX · On-site
$103K - $142K/yr
... RL, and sim-to-real transfer techniques. * A strong intuition for robot dynamics and controls theory, with the ability to apply these principles to guide and constrain learning-based approaches. * A ...
The role of the Readiness Leader (RL) is to provide self-directed, multi-disciplinary technical ... controls from safety basis documents (DSA and TSR) are correctly captured in the documents and are ...
Quick apply
Apply Early
The role of the Readiness Leader (RL) is to provide self-directed, multi-disciplinary technical ... controls from safety basis documents (DSA and TSR) are correctly captured in the documents and are ...
Apply Early
Rl Controls information
See salary details
$19.23 - $21.92
2% of jobs
$21.92 - $24.61
7% of jobs
$24.61 - $27.29
10% of jobs
$28.35 is the 25th percentile. Wages below this are outliers.
$27.29 - $29.98
15% of jobs
The median wage is $32.67 / hr.
$29.98 - $32.67
16% of jobs
$32.67 - $35.36
18% of jobs
$36.95 is the 75th percentile. Wages above this are outliers.
$35.36 - $38.05
12% of jobs
$38.05 - $40.73
10% of jobs
$40.73 - $43.42
6% of jobs
$43.42 - $46.11
3% of jobs
$46.11 - $48.80
1% of jobs
$19
$33
$48
How much do rl controls jobs pay per hour?
As of Jul 2, 2026, the average hourly pay for rl controls in the United States is $33.97, according to ZipRecruiter salary data. Most workers in this role earn between $28.85 and $37.98 per hour, depending on experience, location, and employer.
What is the difference between Rl Controls vs Electrical Controls Technician?
| Aspect | Rl Controls | Electrical Controls Technician |
|---|---|---|
| Certifications | Typically requires PLC programming, control system certifications | Requires electrical certifications, such as NICET or electrical trade licenses |
| Work Environment | Industrial automation, manufacturing plants, control system installation | Industrial, commercial, or manufacturing settings focusing on electrical systems |
| Job Responsibilities | Design, troubleshoot, and program control systems and PLCs | Install, maintain, and repair electrical control panels and systems |
Rl Controls and Electrical Controls Technicians both work in industrial environments and require knowledge of control systems. Rl Controls specialists focus more on programming and system integration, while Electrical Controls Technicians handle electrical wiring and hardware. Both roles are essential in automation and manufacturing industries, often overlapping but with distinct technical focuses.
What are the key skills and qualifications needed to thrive as an RL Controls Engineer, and why are they important?
To thrive as an RL Controls Engineer, you need a solid background in control systems engineering, robotics, and automation, usually supported by a degree in electrical, mechanical, or mechatronics engineering. Familiarity with PLC programming, SCADA systems, HMI software, and relevant certifications like Siemens or Allen-Bradley are commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in troubleshooting and collaborating with cross-functional teams. These skills and qualifications ensure the safe, efficient, and reliable operation of automated systems in industrial environments.
What are 'RL Controls'?
'RL Controls' typically refers to Reinforcement Learning (RL) Controls, which involve using reinforcement learning algorithms to design controllers that optimize the behavior of dynamic systems. In this field, agents learn to make decisions by interacting with environments to maximize cumulative rewards or minimize costs over time. RL Controls are increasingly used in robotics, autonomous vehicles, industrial automation, and other areas where adaptive, data-driven control strategies are valuable. Professionals in this area need a strong foundation in control theory, machine learning, and programming.
What are some common challenges faced by RL Controls Engineers when integrating new automation systems into existing manufacturing environments?
RL Controls Engineers often encounter challenges such as ensuring compatibility between new automation systems and legacy equipment, minimizing downtime during integration, and troubleshooting unforeseen issues during commissioning. Collaboration with cross-functional teams, including mechanical, electrical, and IT departments, is crucial to address these challenges effectively. A proactive approach to documentation and thorough testing helps ensure a smooth transition and long-term reliability of the control systems.
More about Rl Controls jobs
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What states have the most Rl Controls jobs? States with the most job openings for Rl Controls jobs include:
What job categories do people searching Rl Controls jobs look for? The top searched job categories for Rl Controls jobs are:
Full-time
Posted 5 days ago
Job description
Job Summary:
Boston Dynamics is pushing the boundaries of what advanced humanoid robots can do in the real world, and they are seeking a curious, driven Research Scientist to develop cutting-edge reinforcement learning solutions. The role involves designing, training, and deploying RL policies for complex tasks in unstructured environments while collaborating with a world-class team of roboticists.
Responsibilities:
• Design, implement, and train reinforcement learning algorithms for challenging whole-body mobile manipulation and bimanual manipulation tasks.
• Develop high-quality Python and C++ code that is tested, documented, and production-ready.
• Build and leverage high-fidelity simulation environments (e.g., Isaac Sim, MuJoCo) to validate RL policies before deploying on hardware.
• Integrate learned policies with Atlas’s control and software stack through close collaboration with controls and platform teams.
• Deploy, debug, and iterate policies directly on real Atlas hardware through hands-on experimentation.
• Participate in design reviews, experimental planning, and team-wide research direction.
Qualifications:
Required:
• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
• Strong experience training and deploying RL policies for complex behaviors in robots or simulated agents.
• Proficiency with modern ML frameworks (e.g., PyTorch, TensorFlow, RLlib).
• Strong foundations in algorithms, debugging, performance optimization, and robotics fundamentals (kinematics, dynamics).
• Excellent Python and C++ programming skills and experience contributing to production-scale software.
Preferred:
• PhD or equivalent research experience in reinforcement learning or robotic manipulation.
• Experience deploying RL policies on physical robots.
• Experience developing locomotion, bimanual manipulation, or whole-body control behaviors.
• Contributions to large software projects or open-source ML/robotics frameworks.
• Publications in top-tier robotics or ML conferences (e.g., CoRL, RSS, ICRA, NeurIPS).
Company:
Boston Dynamics is an engineering company that specializes in building dynamic robots and software for human simulation. It is a sub-organization of Hyundai Motor Company. Founded in 1992, the company is headquartered in Waltham, USA, with a team of 501-1000 employees. The company is currently Late Stage.
Boston Dynamics is pushing the boundaries of what advanced humanoid robots can do in the real world, and they are seeking a curious, driven Research Scientist to develop cutting-edge reinforcement learning solutions. The role involves designing, training, and deploying RL policies for complex tasks in unstructured environments while collaborating with a world-class team of roboticists.
Responsibilities:
• Design, implement, and train reinforcement learning algorithms for challenging whole-body mobile manipulation and bimanual manipulation tasks.
• Develop high-quality Python and C++ code that is tested, documented, and production-ready.
• Build and leverage high-fidelity simulation environments (e.g., Isaac Sim, MuJoCo) to validate RL policies before deploying on hardware.
• Integrate learned policies with Atlas’s control and software stack through close collaboration with controls and platform teams.
• Deploy, debug, and iterate policies directly on real Atlas hardware through hands-on experimentation.
• Participate in design reviews, experimental planning, and team-wide research direction.
Qualifications:
Required:
• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field.
• Strong experience training and deploying RL policies for complex behaviors in robots or simulated agents.
• Proficiency with modern ML frameworks (e.g., PyTorch, TensorFlow, RLlib).
• Strong foundations in algorithms, debugging, performance optimization, and robotics fundamentals (kinematics, dynamics).
• Excellent Python and C++ programming skills and experience contributing to production-scale software.
Preferred:
• PhD or equivalent research experience in reinforcement learning or robotic manipulation.
• Experience deploying RL policies on physical robots.
• Experience developing locomotion, bimanual manipulation, or whole-body control behaviors.
• Contributions to large software projects or open-source ML/robotics frameworks.
• Publications in top-tier robotics or ML conferences (e.g., CoRL, RSS, ICRA, NeurIPS).
Company:
Boston Dynamics is an engineering company that specializes in building dynamic robots and software for human simulation. It is a sub-organization of Hyundai Motor Company. Founded in 1992, the company is headquartered in Waltham, USA, with a team of 501-1000 employees. The company is currently Late Stage.
About Boston Dynamics
Sourced by ZipRecruiter
Industry
Industrial automation equipment manufacturing
Company size
51 - 200 Employees
Headquarters location
Waltham, MA, US
Year founded
1992