Machine Learning, Robotics Engineer – Simulation

This is a fully remote position, open to applicants in Uruguay.

📋 Description

• Design and assess machine learning and robotics solutions from initial experimentation through to production implementation.

• Create and utilize simulated environments to evaluate algorithms, produce synthetic data, and analyze system performance.

• Develop workflows for data gathering, processing, training, and assessment.

• Integrate models with sensors, software platforms, and hardware as necessary.

• Craft experiments to evaluate performance, comprehend failure modes, and measure the transfer from simulation to real-world applications.

• Work in collaboration with engineers, researchers, and clients to convert project needs into effective solutions.

• Write maintainable code and contribute to reusable tools and engineering practices across various projects.

⛳️ Requirements

• Proven experience in machine learning engineering, robotics, or a closely related discipline.

• Practical experience with a simulation platform such as NVIDIA Isaac Sim, Isaac Lab, MuJoCo, Gazebo, PyBullet, or a similar tool.

• Proficient in Python programming with a solid foundation in software engineering principles.

• Experience in developing and assessing ML models or robotics algorithms, with an understanding of validation and performance metrics.

• Knowledge of sensor modeling, coordinate transformations, kinematics, dynamics, or physics-based simulation.

• Comfortable working with Linux, Git, and collaborative development processes.

• Ability to tackle open-ended challenges, communicate trade-offs, and take responsibility for implementation and validation.

• Plus: knowledge in computer vision, 3D perception, or multimodal learning.

• Plus: experience in synthetic data generation, domain randomization, or sim-to-real evaluation.

• Plus: familiarity with reinforcement learning, imitation learning, motion planning, or control.

• Plus: experience with ROS/ROS 2 and integration with physical sensors or robots.

• Plus: deployment experience on edge devices such as NVIDIA Jetson.

• Plus: knowledge of C++, GPU optimization, Docker, or cloud infrastructure.

• Plus: experience transitioning prototypes into reliable production systems.

🏝️ Benefits

• No specific benefits, perks, or compensation extras mentioned.