ML Engineer

What We’re Looking For

• 2+ years of hands-on experience in Machine Learning / Computer Vision.
• Strong knowledge of Deep Learning architectures (CNNs, object detection, segmentation).
• Solid skills with PyTorch / TensorFlow, ONNX, and OpenCV.
• Experience with model deployment on embedded hardware (e.g., NVIDIA Jetson, Coral TPU, ARM SoCs).
• Familiarity with model optimization frameworks: TensorRT, TFLite, OpenVINO.
• Strong Python skills for prototyping and pipelines; knowledge of C/C++ or Rust for integration is a big plus.
• Experience with Linux-based development environments and version control (Git).
• Bonus: exposure to MLOps tools (Docker, CI/CD for ML).
   

What You’ll Do

• Design, train, and optimize Computer Vision models (detection, tracking, classification, segmentation).
• Build and maintain training pipelines and support data re-capturing workflows.
• Deploy and optimize models for embedded/edge devices (low-latency, low-power environments). 
• Apply model optimization techniques (quantization, pruning, knowledge distillation).
• Collaborate closely with embedded engineers to integrate ML into device firmware.
• Research and implement state-of-the-art methods in CV and Edge AI.
   

What We Offer

• A chance to work on an innovative embedded AI product with real-world impact.
• Competitive compensation.
• Full remote, flexible schedule.
• A team that values technical excellence, ownership, and creativity.
• Opportunity to shape the system architecture and influence key decisions.