OpenRecently verified

Robotics ML Expert - MuJoCo Simulation Environments

  • Data & Machine Learning
  • Platform: Alignerr

$100-150/hrAs published by the platform.

About this job

This contract role centers on building and refining MuJoCo physics simulation environments where AI agents learn locomotion, manipulation, and multi-agent coordination. It suits experienced robotics and machine learning practitioners who can combine reinforcement learning, robot control, and simulation debugging. Work is remote, asynchronous, and organized around milestones.

What you'll do

  • Design and iterate on MuJoCo simulation environments for robotics research and AI training.
  • Implement and tune reinforcement learning algorithms to train agents in simulated tasks.
  • Define reward functions, observation spaces, and action spaces for robust policies.
  • Debug and optimize contact models, actuator dynamics, and scene configurations.

Requirements

PythonPyTorchMachine Learning

    Pay

    $100-150/hr

    Pay as published by the platform. It is not a guarantee of income or hours.

    Location

    The platform has not published which countries are eligible for this job.

    How to apply

    You apply on Alignerr, Labelbox's expert network: create a profile, complete an AI-led interview and skills assessment, then get matched to projects in your field.

    All Alignerr jobs and how the platform works

    Source

    Official posting: https://www.alignerr.com/jobs/e20e6280-0440-4b58-9969-2b8b143d3f9e

    Last checked on October 8, 2026.

    Similar jobs

    • Data & Machine Learning
    • Platform: Alignerr

    This remote contract role asks you to build and refine MuJoCo simulation environments that teach AI agents locomotion, manipulation, and multi-agent coordination. It is aimed at experienced robotics and machine learning practitioners who are comfortable with physics simulation, reinforcement learning, and robot control.

    OpenRecently verified$100-150/hr
    • Data & Machine Learning
    • Platform: Alignerr

    This contract role centers on building and refining MuJoCo physics simulation environments where AI agents learn locomotion, manipulation, and multi-agent coordination. It suits experienced robotics and machine learning practitioners who work on reinforcement learning, robot control, and simulation debugging, mostly on their own in an asynchronous, remote setting.

    OpenRecently verified$100-150/hr
    • Data & Machine Learning
    • Platform: DataAnnotation

    As a Machine Learning Engineer, you will evaluate and improve how AI models reason about machine learning systems, including training dynamics, evaluation design, and deployment strategies. You will write prompts to test model reasoning, identify subtle errors in AI outputs, and provide correct solutions based on real practitioner experience.

    Talent poolRecently verified$40-150/hr
    • Data & Machine Learning
    • Platform: Turing
    • Location: Worldwide
    • Language: English
    • Level: Intermediate
    • Commitment: 40 hrs/week

    Design and optimization of deep learning systems, statistical analysis and training of ML models for Turing clients, remote work with time overlap with US time zones.

    Talent poolRecently verifiedPay not disclosed
    • Data & Machine Learning
    • Platform: Mercor
    • Location: United States
    • Level: Intermediate

    This role involves designing and evaluating MLOps infrastructure tasks for training large language models, in the areas of GPU programming, performance profiling, debugging distributed workloads, and high-performance inference. You will generate quality training data by writing precise technical solutions and providing detailed feedback to research and engineering teams. This role targets engineers with confirmed hands-on expertise in ML systems and infrastructure, capable of reasoning about trade-offs between throughput, latency, and memory on modern accelerators.

    Posted September 15, 2026

    OpenRecently verified$90-120/hr

    Referral link: we may earn a fee. Apply without it

    Keep exploring