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Marvik
Marvik
51 – 200 Employees
ConsultingHealthcareLogistics
Marvik is a technology consultancy focused on turning artificial intelligence into production systems for enterprise organizations. Its team works across AI strategy, opportunity discovery, data engineering, model development, generative AI, LLMs, AI agents, computer vision, predictive analytics, robotics, and automation. Marvik also provides access to senior AI expertise and fractional leadership, helping organizations develop scalable solutions for sectors including retail, e-commerce, logistics, fintech, manufacturing, healthcare, energy, and government.
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Machine Learning and Robotics Engineer, Simulation

Build and validate simulated machine learning and robotics systems for physical-world applications at Marvik. Work across robotics, perception, synthetic data, and model development from experimentation through production.

UYUruguayRemoteFull-timeMiddleSeniorEnglish RequiredMachine Learning Engineer
C++CloudDockerLinuxPython

Description

  • Develop and assess machine learning and robotics solutions from initial experiments through production integration
  • Create and operate simulation environments for algorithm testing, synthetic data generation, and system evaluation
  • Build data pipelines covering collection, processing, model training, and evaluation
  • Connect models with sensors, software platforms, and hardware as project needs require
  • Plan experiments that measure performance, identify failure modes, and evaluate simulation-to-real-world transfer
  • Partner with engineers, researchers, and clients to turn project requirements into practical implementations
  • Produce maintainable code and reusable tools while strengthening engineering practices across projects

Requirements

  • Professional 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 an equivalent tool
  • Strong Python skills combined with sound software engineering practices
  • Experience developing and evaluating machine learning models or robotics algorithms, including validation methods and performance metrics
  • Working knowledge of sensor modeling, coordinate transformations, kinematics, dynamics, or physics-based simulation
  • Comfortable using Linux and Git within collaborative development processes
  • Able to handle open-ended challenges, explain trade-offs, and own implementation and validation work
  • Additional experience in computer vision, 3D perception, or multimodal learning is advantageous
  • Additional experience with synthetic data generation, domain randomization, or sim-to-real evaluation is advantageous
  • Additional experience with reinforcement learning, imitation learning, motion planning, or control is advantageous
  • Additional experience with ROS or ROS 2 and physical sensor or robot integration is advantageous
  • Additional experience deploying systems to edge devices such as NVIDIA Jetson is advantageous
  • Additional experience with C++, GPU optimization, Docker, or cloud infrastructure is advantageous
  • Additional experience converting prototypes into dependable production systems is advantageous

Benefits

  • No explicit benefits, perks, or additional compensation details are provided

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