← Todas las ofertas

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.

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
108

Inversores mencionados

Detalles de la oferta

La descripción completa publicada por Harmattan AI.

Ver la oferta original ↗

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.

As an ML Research Engineer in the Visual Navigation team, you will join us at an early stage to heavily influence our technical direction. Operating out of Paris, Lausanne or Zurich, you will focus on developing Machine Learning models to enable our drones to navigate on the battlefield, with responsibilities ranging from data curation and model architecture definition to onboard inference on our drones.

Responsibilities

DL Algorithm Development: Design deep learning models to analyze a drone's environment in multiple modalities and enable its localization through time and space.

  • Edge AI Optimization: Embed models on heterogeneous platforms with limited shared compute. Optimize trade-offs between model speed and accuracy to minimize pipeline latency.
  • Cross-Team Collaboration: Partner with the VIO, Navigation, and Embedded Software teams to build a robust, real-time localization pipeline, communicating trade-offs clearly to stakeholders.
  • Research & Innovation: Stay at the absolute forefront of scientific trends in Deep Learning to introduce cutting-edge methodologies to the team.
  • Pipeline Management & MLOps: Build, heavily modify, and manage training, evaluation, and MLOps pipelines while ensuring reproducibility, robust logging, and version control.
  • Validation & Field Testing: Actively participate in real-world flight tests. Analyze in-field failures to continuously iterate and improve deployed models. Candidate

Requirements

Educational Background: Strong academic record with a STEM degree (e.g., Computer Science, Machine Learning, Robotics, Mathematics).

  • Deep Learning & Computer Vision Expertise: Proven track record of researching and productizing Deep Learning models for Computer Vision in the industry (Drones, Robotics, Autonomous Vehicles, etc.)
  • Technical Competence: Proficiency in Python and DL frameworks (PyTorch/Lightning). Experience with MLOps and edge deployment optimization. Professional Attributes:
  • Highly structured, analytical, and research-oriented.
  • Excellent communicator able to translate complex algorithmic benchmarking to downstream users and stakeholders.
  • Thrives in a fast-paced environment with a hands-on, “no-task-is-too-small” mentality.
  • Commitment: 100% dedication to Harmattan AI’s mission, vision, and growth plans, ready to go the extra mile for operational excellence. We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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.