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(02 / 10 / 2025) RL Research Engineer

(02 / 10 / 2025) RL Research Engineer

MerilIndia
8 hours ago
Job description

Job Title : RL Research Engineer (Planning & Control)

Location : Vapi, Gujarat

Employment Type : Full-Time

Overview

We 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 Responsibilities

  • Develop 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-Haves

  • 4–8+ 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-Haves

  • Experience with multi-agent reinforcement learning.
  • Knowledge of hierarchical options and diffusion policies.
  • Familiarity with long-horizon task planning in complex environments.
  • Success Metrics

  • Task 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 Notes

    Humanoids :

  • 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 Instructions

    Interested 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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