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RL Research Engineer

  • ... Posted on: Feb 23, 2026
  • ... Meril
  • ... Vapi, Gujarat
  • ... Salary: Not Available
  • ... Full-time

RL Research Engineer   

Job Title :

RL Research Engineer

Job Type :

Full-time

Job Location :

Vapi Gujarat United States

Remote :

No

Jobcon Logo Job Description :

Job Title: RL Research Engineer (Planning & Control) Location: Vapi, Gujarat Employment Type: Full-TimeOverviewWe are seeking a highly skilled Reinforcement Learning (RL) Research Engineer specializing in planning and control. The role focuses on designing learning-based planners and policies (RL, imitation learning, model-based) and integrating them with classical control approaches to enable safe, efficient, and robust autonomous operation across multiple domains including humanoids, AGVs, cars, and drones.Key ResponsibilitiesDevelop and train policies from human demonstrations and teleoperation data.Implement safe reinforcement learning approaches with constraints.Design long-horizon planners using world models and uncertainty-aware control.Implement safety shields, fallback controllers, and verify-before-deploy pipelines.Collaborate with cross-functional teams to integrate RL policies with control systems.Conduct sim-to-real transfer and ensure policies generalize in real-world settings.Design reward functions and implement offline RL and behavioral cloning strategies.Must-Haves4–8+ years of experience in RL and control systems.Strong expertise in Model Predictive Control (MPC), Control Barrier Functions (CBFs), reachability analysis, or similar methods.Master’s or PhD in Robotics, Control, AI, or a related field.Experience with sim-to-real transfer, reward design, offline RL, and behavioral cloning.Nice-to-HavesExperience with multi-agent reinforcement learning.Knowledge of hierarchical options and diffusion policies.Familiarity with long-horizon task planning in complex environments.Success MetricsTask success rate in target domains.Rate of human or system interventions during execution.Compliance with energy, jerk, and other control limits.Minimization of constraint violations in real-world deployment.Domain NotesHumanoids: - Stable locomotion and bimanual task RL.AGVs (Autonomous Ground Vehicles): - Navigation in mixed human zones, traffic rule compliance, and aisle etiquette.Cars: - Interactive merges, handling unprotected turns, and safe navigation in dynamic traffic.Drones: - Wind-robust flight, safe landing and perching maneuvers.Application InstructionsInterested candidates may apply by sending their resume and cover letter to parijat.patel@merai.co with the subject line: “RL Research Engineer (Planning & Control) Application”.

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Jobcon Logo Position Details

Posted:

Feb 23, 2026

Reference Number:

15820_4292178096

Employment:

Full-time

Salary:

Not Available

City:

Vapi

Job Origin:

APPCAST_CPC

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Job Title: RL Research Engineer (Planning & Control) Location: Vapi, Gujarat Employment Type: Full-TimeOverviewWe are seeking a highly skilled Reinforcement Learning (RL) Research Engineer specializing in planning and control. The role focuses on designing learning-based planners and policies (RL, imitation learning, model-based) and integrating them with classical control approaches to enable safe, efficient, and robust autonomous operation across multiple domains including humanoids, AGVs, cars, and drones.Key ResponsibilitiesDevelop and train policies from human demonstrations and teleoperation data.Implement safe reinforcement learning approaches with constraints.Design long-horizon planners using world models and uncertainty-aware control.Implement safety shields, fallback controllers, and verify-before-deploy pipelines.Collaborate with cross-functional teams to integrate RL policies with control systems.Conduct sim-to-real transfer and ensure policies generalize in real-world settings.Design reward functions and implement offline RL and behavioral cloning strategies.Must-Haves4–8+ years of experience in RL and control systems.Strong expertise in Model Predictive Control (MPC), Control Barrier Functions (CBFs), reachability analysis, or similar methods.Master’s or PhD in Robotics, Control, AI, or a related field.Experience with sim-to-real transfer, reward design, offline RL, and behavioral cloning.Nice-to-HavesExperience with multi-agent reinforcement learning.Knowledge of hierarchical options and diffusion policies.Familiarity with long-horizon task planning in complex environments.Success MetricsTask success rate in target domains.Rate of human or system interventions during execution.Compliance with energy, jerk, and other control limits.Minimization of constraint violations in real-world deployment.Domain NotesHumanoids: - Stable locomotion and bimanual task RL.AGVs (Autonomous Ground Vehicles): - Navigation in mixed human zones, traffic rule compliance, and aisle etiquette.Cars: - Interactive merges, handling unprotected turns, and safe navigation in dynamic traffic.Drones: - Wind-robust flight, safe landing and perching maneuvers.Application InstructionsInterested candidates may apply by sending their resume and cover letter to parijat.patel@merai.co with the subject line: “RL Research Engineer (Planning & Control) Application”.

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