Machine Learning Engineer (Detect & Track Distillation)
Harmattan AI2 months ago
Paris, France or Zürich, SwitzerlandSenior
Responsibilities
- Distill and fine-tune large foundation models into efficient components for detection and other specialized tasks.
- Optimize neural networks for constrained embedded systems using quantization, pruning, and LoRA.
- Build, modify, and manage reproducible training, evaluation, and MLOps pipelines with robust logging and version control.
- Curate data and create task-specific datasets to improve model accuracy.
- Benchmark distilled models for performance and latency in real-world operational deployments.
- Research advances in computer vision and quantization and introduce relevant methodologies.
- Collaborate with foundation, systems, project, and mission-intelligence teams.
- Depending on seniority, manage or mentor junior engineers.
Requirements
- A strong academic record and a degree in a STEM field such as Computer Science, Engineering, or Mathematics.
- Proven experience running vision neural networks, developing target-detection architectures, or managing re-identification tasks.
- Hands-on expertise in knowledge distillation, model compression, and deploying networks to constrained embedded or edge hardware such as Jetson or custom NPUs.
- Proficiency in MLOps, GPU compute, and building infrastructure such as training-pipeline templates and loggers.
- Strong analytical, structured, research-oriented, communication, and stakeholder-influence skills.
- Ability to work under pressure in a fast-paced environment and contribute to foundational team infrastructure.
- Full commitment to Harmattan AI’s mission and operational requirements.
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