Machine Learning Engineer (Detect & Track Distillation)

ph3About Us /h3 pHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. /p pOur work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. /p h3About The Role /h3 pHarmattan AI is heavily pushing the boundaries of autonomous systems, where the perception of the surrounding world through visual cues is a vital component. To make sense of incoming visual data and enable mission-critical downstream decisions, we have developed custom detection models.

As our product and project portfolio expands, we are diversifying our efforts in this space across multiple embedded platforms. /p pAs an ML Research Engineer in the bDetectTrack Distillation /b team, you will join us at a very early stage, giving you a unique opportunity to heavily influence the technical direction of the team. Operating out of bLausanne, Paris, or Zurich /b, you will focus on taking large foundation models and distilling them into highly optimized, task-specific components.

Your work will span target detection, classification, and target re-identification across time, directly tackling the hardware inference constraints of diverse edge and embedded systems. /p h3Responsibilities /h3 ul liModel Distillation Finetuning: Take large foundation models and compress/distill them into highly specific, efficient components optimized for smaller tasks and target detection. /li liEdge AI Optimization: Optimize neural networks for constrained embedded systems using techniques such as quantization (PTQ vs. QAT), pruning, and LoRA. /li liPipeline Management MLOps: Build, heavily modify, and manage training, evaluation, and MLOps pipelines while ensuring reproducibility, robust logging, and version control. /li liData Curation: Collaborate on data curation and the creation of task-specific datasets to constantly improve model accuracy. /li liBenchmarking Evaluation:

Framework-level benchmarking of newly distilled models to evaluate performance and latency, ensuring results are fully aligned with real-world operational deployments. /li liResearch Innovation: Stay at the absolute forefront of scientific trends in computer vision and quantization research to introduce cutting-edge methodologies to the team. /li liCross-Functional Collaboration: Work closely with the DetectTrack Foundation team, downstream System Engineers, Project Teams, and Mission Intelligence to deliver robust solutions. /li liMentorship: Depending on seniority, support the team by managing or mentoring junior engineers. /li /ul h3Candidate Requirements /h3 ul liEducational Background: A strong academic record with a degree in a STEM field (e.g., Computer Science, Engineering, Mathematics). /li liDeep Learning Computer Vision: Proven experience running vision neural networks,

developing target detection architectures, or managing re-identification tasks. /li liModel Compression Edge AI: Hands-on expertise in knowledge distillation, model compression, and deploying networks onto highly constrained embedded systems or edge hardware (e.g., Jetson, custom NPUs, wearables). /li liTechnical Competence Infrastructure: Proficiency in MLOps, GPU compute, and building infrastructure (such as training pipeline templates and loggers). /li liProfessional Attributes: /li ul liHighly structured, analytical, task-aligned, and research-oriented. /li liExcellent communication and influence skills, with the ability to effectively translate and present complex benchmarking data to downstream users and senior stakeholders. /li liThrives under pressure in a fast-paced environment with a “no-task-is-too-small” mentality toward building foundational team infrastructure. /li /ul

liCommitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence /li /ul pWe look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI. /p /p