Spontaneous Application - Senior ML Engineering

Join our team as a Senior ML Engineer, where you'll work closely with research scientists on deep learning experimentations and help scale our MLops infrastructure. You'll be responsible for training and evaluating deep learning models, building pipelines for experimentation and reproducibility, scaling ML workflows, and supporting research teams in fast-moving environments. Strong ML engineering skills, experience with diverse data types, good software habits, a team-first mindset, and a curiosity for science-driven environments are essential.

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Indefinido
Paris
Unos días en casa
Salario: No especificado
Experiencia: > 5 años
Formación: Licenciatura / Máster
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Collaborate closely with Research Scientists to design, implement, and evaluate deep learning models for various applications.

Build and maintain robust pipelines and infrastructure for experimentation, ensuring reproducibility and scalability of ML workflows.

Support research teams by managing real-world data, scaling ML workflows, and providing technical expertise in fast-moving environments.

Sigma Nova
Sigma Nova

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El puesto

Descripción del puesto

We are looking for talented ML/Resaerch Eng people who are as excited to work closely with Research Scientist on Deep Learning experimentations as they are on the idea of scaling our MLops Infrastructure.


Requisitos

We’re looking to meet ML engineers who love turning complex models into working systems and collaborating across research and product. You may have experience in:

  • Training and evaluating deep learning models (vision, time series, neurodata, etc.)

  • Building pipelines and infrastructure for experimentation and reproducibility

  • Scaling ML workflows and managing real-world data

  • Supporting research teams in fast-moving environments

You’re hands-on, collaborative, and excited by the idea of building the ML backbone of science-native AI systems.

  • 🛠️ Strong ML engineering skills (Python, PyTorch, JAX, etc.)

  • 📦 Experience working across diverse data types or scientific modalities

  • 🔁 Good software habits: versioning, testing, clean code

  • 🤝 Team-first mindset and ability to work across functions

  • 🌱 Curiosity and desire to work in a science-driven environment


Proceso de selección

Will be communicated soon , potentially with different job descriptions for different roles

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