Harmattan AI desarrolla sistemas autónomos y software de gestión de misiones para la defensa. Entre sus clientes figuran fuerzas armadas y empresas industriales, que los utilizan para ISR, interceptación de drones y guerra electrónica.
Machine Learning Engineer (Detect & Track Distillation)
Harmattan AI busca un ingeniero de aprendizaje automático para el equipo Detect & Track Distillation, con sede en París. La función consiste en destilar y optimizar modelos de visión para sistemas embebidos con recursos limitados, especialmente mediante cuantificación, poda y LoRA. El puesto también abarca los pipelines MLOps, la curación de datos y la evaluación del rendimiento y la latencia de los modelos.
Datos sobre Harmattan AI
- Modelo
- B2B
- Tipo de empresa
- Financiada con capital riesgo
- Fase
- Unicornio
- Sede
- Paris
- Dominio oficial
- harmattan.ai
- Fundación
- 2024 · 2 años
- Plantilla publicada
- 226 empleados
- Valoración publicada
- 1,4 Md$Fuente ↗
- Última ronda
- Series B · 2026-01-12
- Importe anunciado
- 200 000 000 $
- Ofertas abiertas
- 106
Inversores mencionados
Detalles de la oferta
La descripción completa publicada por Harmattan AI.
About us
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.
About the role
Harmattan 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.
As an ML Research Engineer in the Detect & Track Distillation 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 Lausanne, Paris, or Zurich, 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.
Responsibilities
Model Distillation & Finetuning: Take large foundation models and compress/distill them into highly specific, efficient components optimized for smaller tasks and target detection.
- Edge AI Optimization: Optimize neural networks for constrained embedded systems using techniques such as quantization (PTQ vs. QAT), pruning, and LoRA.
- Pipeline Management & MLOps: Build, heavily modify, and manage training, evaluation, and MLOps pipelines while ensuring reproducibility, robust logging, and version control.
- Data Curation: Collaborate on data curation and the creation of task-specific datasets to constantly improve model accuracy.
- Benchmarking & Evaluation: Framework-level benchmarking of newly distilled models to evaluate performance and latency, ensuring results are fully aligned with real-world operational deployments.
- Research & Innovation: Stay at the absolute forefront of scientific trends in computer vision and quantization research to introduce cutting-edge methodologies to the team.
- Cross-Functional Collaboration: Work closely with the Detect&Track Foundation team, downstream System Engineers, Project Teams, and Mission Intelligence to deliver robust solutions.
- Mentorship: Depending on seniority, support the team by managing or mentoring junior engineers.
Candidate requirements
Educational Background: A strong academic record with a degree in a STEM field (e.g., Computer Science, Engineering, Mathematics).
- Deep Learning & Computer Vision: Proven experience running vision neural networks, developing target detection architectures, or managing re-identification tasks.
- Model 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).
- Technical Competence & Infrastructure: Proficiency in MLOps, GPU compute, and building infrastructure (such as training pipeline templates and loggers).
- Professional Attributes:
- Highly structured, analytical, task-aligned, and research-oriented.
- Excellent communication and influence skills, with the ability to effectively translate and present complex benchmarking data to downstream users and senior stakeholders.
- Thrives under pressure in a fast-paced environment with a “no-task-is-too-small” mentality toward building foundational team infrastructure.
- Commitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.
Requisitos
- titulación en un campo STEM
- Aprendizaje profundo y visión por ordenador
- compresión de modelos
- IA en el borde
Inscribirme en esta oferta
¿Cómo inscribirme?
La oferta está publicada en el sitio de Harmattan AI. Abre la oferta original ↗ para enviar tu candidatura. Screeningpass no rellena formularios por ti.
¿A quién escribir en Harmattan AI para este puesto?
Inicia una búsqueda de contacto desde esta página. Screeningpass te propone hasta tres personas vinculadas al puesto. Tú eliges a quién escribir y Screeningpass busca su correo profesional y prepara un mensaje. Lo revisas y lo envías tú con Gmail. No siempre hay una dirección de correo disponible y nunca se garantiza una respuesta.
¿Cuánto cuesta buscar un contacto?
Una búsqueda cuesta 1 crédito. Se te devuelve si la búsqueda falla. Al registrarte recibes 3 créditos, para hacer 3 búsquedas.
¿Para qué sirve Screeningpass?
Screeningpass reúne ofertas de prácticas, formación dual y empleo publicadas por las empresas. Para una oferta, Screeningpass encuentra una persona con la que contactar en la empresa, busca su correo profesional y prepara un mensaje a partir de tu CV. Ver el funcionamiento en detalle.