Social network you want to login/join with:
col-narrow-left
Location:
Job Category:
-
col-narrow-right
Job Reference:
ecr65wsp-216083
Job Views:
2
Posted:
26.04.2025
Expiry Date:
10.06.2025
col-wide
Job Description:
TechBiz Global is a leading recruitment and software development company. Our diverse, globally distributed team provides IT recruitment, outstaffing, outsourcing, software development, and consulting services with a primary focus on helping our partners achieve their business goals successfully.
With headquarters in Germany, we serve successful clients worldwide. We understand your unique needs, and our team has hands-on experience with the challenges of rapid growth and the IT sector. All our offerings are built with a tech mindset.
We are seeking a Foundation Model Scientist/Engineer for a hybrid role, preferably based in Paris. Join us to create cutting-edge solutions that drive significant business impact.
What You’ll Do
* Develop and optimize the training and inference stack for Vision-Language-Action foundation models in robotics
* Collaborate with simulation and real-world robotics teams to curate high-quality, diverse, and large-scale datasets
* Design new generative simulation techniques to expand simulation data scale and diversity, training and evaluating generative models of 3D objects and environments, and language/code models to generate tasks and reward functions
* Work with a team committed to building general-purpose Physical AI
What You’ll Bring
* Passion for your craft and demonstrated excellence in foundation model research and engineering
* Exceptional ownership and initiative—finding and solving problems independently
* Extensive experience pioneering new machine learning ideas or refining existing methods, supported by first-author publications or impactful projects (5+ years)
* A relentless commitment to data and code quality, rigorous evaluation, and meticulous attention to detail
* Production-level expertise in modern Python
Bonus: Experience with Vision-Language-Action models for robotics or web agents
#J-18808-Ljbffr