Marvik
AI & Robotics Engineer
MarvikArgentina5 days ago
Full-timeEngineering, Information Technology
We are looking for a Machine Learning Engineer with experience building and deploying perception and sensor-based ML systems in robotics or autonomous platforms. The role involves working across the full lifecycle of data, models, and deployment—from raw sensor streams to production-ready perception modules.

This is a great fit for someone who has worked with LiDAR, cameras, radar, IMUs, or multimodal pipelines, and who enjoys taking ML systems from prototype to field-tested reality.

🧑🏻‍💻 Key Responsibilities

Perception & Sensor Fusion

  • Develop ML pipelines for multimodal sensor data (LiDAR, cameras, radar, IMU, etc.).
  • Implement or support sensor fusion approaches (classical or ML-based).
  • Build models and processing steps for perception tasks such as detection, tracking, mapping, or scene understanding.

Cross-Functional Collaboration

  • Work closely with robotics engineers, software teams, and simulation teams to ensure seamless integration of ML perception modules.
  • Contribute to design discussions involving sensing hardware, data capture strategies, and operational requirements.

Model Development & Deployment

  • Train, evaluate, and optimize ML models for robotics perception under real-world constraints.
  • Deploy ML components to diverse environments (edge devices, robotics stacks, cloud backends).
  • Collaborate on performance tuning, latency improvements, and reliability enhancements.

🤝 If you have

  • Experience working with robotics or autonomous systems.
  • Hands-on work with LiDAR, cameras, radar, or IMU pipelines.
  • Strong Python and ML fundamentals, with experience in at least one major framework (PyTorch, TensorFlow).
  • Experience designing or maintaining sensor-based ML systems, including data preparation and evaluation.
  • Understanding of model deployment in real systems (edge devices, robotics stacks, embedded platforms, or cloud).

🦾 It’s a plus

  • Experience with sensor fusion frameworks, classical or ML-based.
  • Familiarity with robotics middleware (ROS/ROS2), mapping, SLAM, or navigation stacks.
  • Exposure to simulation tools (Isaac Sim, Gazebo, Unity, Webots).
  • Experience improving performance of models under real-time constraints.
  • Background working with safety, reliability, or high-availability systems.

Key Skills

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