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Harmattan 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.
Our 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.
Responsabilities
- Design and implementation of deep learning models for computer vision tasks.
- Research and experimentation with CNNs and Vision Transformers.
- Model compression techniques such as knowledge distillation.
- Quantisation-aware training (QAT) and post-training quantisation (PTQ).
- Network and dataset pruning strategies.
- Design of efficient architectures for edge and embedded systems.
- Dataset curation, balancing, and bias mitigation.
- Experimental design, ablation studies, and reproducibility practices.
- Robust evaluation using appropriate metrics (e.g., mAP, IoU, calibration).
- Failure case analysis and robustness testing under distribution shifts.
Requirements
- Technical Background: Solid foundation in Deep Learning (preferably PyTorch).
- Experience with CNNs and/or Transformers (academic or project-based).
- Understanding of bias–variance trade-offs and generalisation.
- Familiarity with optimisation fundamentals and basic probability.
- Experience or strong interest in model compression techniques.
- Interest in hardware-aware and efficient model design.
- Experience with ONNX, TensorRT, TFLite or LiteRT.
- Familiarity with experiment tracking tools (e.g., W&B, MLflow).
- Experience conducting ablation studies.
- Exposure to dataset curation or annotation processes.
- Prior participation in research projects or conference work.
- Hands-on research experience in applied computer vision.
- Exposure to model optimisation and edge deployment challenges.
- Experience reading, implementing, and evaluating cutting-edge research.
- Mentorship from experienced researchers and engineers.
- Opportunity to contribute to publications or conference submissions.
We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.
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