Machine Learning Engineer (Edge AI & Computer Vision)

MarvikColorado Springs, CO
Remote

About The Position

Want to work with cutting-edge technologies on long-term, strategic projects that combine Deep Learning, Computer Vision, Edge AI, and IoT? At Marvik, we are leading the next evolution of smart machinery—integrating vision capabilities, real-time image processing, and multi-sensor fusion into physical products operating in real environments.

Requirements

  • Strong experience bringing AI to production: It’s not just about training models—you know how to make them run reliably in real-world environments.
  • Solid background in AI & Deep Learning, including experience with LLMs, Computer Vision, multimodal models, model optimization, and efficient inference.
  • Edge AI & Embedded exposure: Experience optimizing models for constrained devices (TensorRT, ONNX, OpenCV, C++, or Python).
  • Strong Ownership & Soft Skills: Highly collaborative, proactive, independent, and clear in technical communication. A team player who builds trust with clients and peers.
  • Advanced English level: Excellent verbal and written communication skills to interact directly with international client teams.
  • Required tools: Python, C++, PyTorch/TensorFlow, OpenCV, Docker, Git.

Nice To Haves

  • Hands-on experience with NVIDIA Jetson, ROS/ROS2, or embedded hardware platforms.
  • Experience in domains such as Robotics, IoT, Drones, Automotive, or Industrial Machinery.
  • Knowledge of sensor fusion (IMU, cameras, LiDAR) or OTA (Over-The-Air) updates and Cloud IoT architectures (AWS/Azure IoT).

Responsibilities

  • Take end-to-end ownership of Machine Learning models, moving them beyond training and ensuring reliable deployment in production on physical hardware.
  • Design, build, and optimize real-time AI pipelines, integrating foundation models, sensor and application data, and scalable inference workflows.
  • Optimize inference performance, memory usage, and execution speed for Edge AI platforms (e.g., NVIDIA Jetson, embedded platforms).
  • Collaborate directly with clients and cross-functional engineering teams, building trust, proposing proactive solutions, and maintaining smooth technical communication.
  • Debug, monitor, and maintain production models operating continuously under real-world hardware constraints.

Benefits

  • Challenging, real-world projects
  • State-of-the-art tech stack
  • Strategic growth
  • Great team culture
  • Flexible work style: Opportunity to work remotely with global, high-impact clients.
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