Our github: https://github.com/helicalAI/helical/

Our Website: https://www.helical-ai.com/

Your Role

As a Machine Learning Engineer - Scaling at Helical, you’ll build, optimize, and scale real-world applications of bio foundation models

You’ll work closely with researchers and product engineers to productionize model training, inference, and deployment workflows. You’ll also help push the limits of foundation models by prototyping new methods, contributing to our core ML infrastructure, and translating research into fast, iterative code.

This is a deeply technical role with high ownership — ideal for engineers who want to operate at the bleeding edge of AI infrastructure, model development, and system design.

What You’ll Do

• Build and maintain scalable training/inference pipelines for foundation models (e.g. Transformers, SSMs).
• Optimize model performance, latency, and throughput across environments.
• Design modular, reusable ML components for internal and open-source use.
• Collaborate with researchers to scale notebooks into production-grade systems.
• Own ML infrastructure components (data loading, distributed compute, experiment tracking, etc.).

Requirements

Essentials

• MSc or PhD in Machine Learning, Computer Science, Applied Math, or similar.
• Strong Python programming skills, with deep knowledge of PyTorch, JAX, or TensorFlow.
• Hands-on experience building and scaling ML pipelines in real-world settings.
• Comfort with MLOps tools and practices (e.g. Weights & Biases, Ray, Docker, etc.).
• Experience with modern ML architectures — Transformers, Diffusion Models, SSMs, etc.
• High agency, fast iteration speed, and comfort with ambiguity in early-stage environments

Bonus Points

• Contributions to open-source ML libraries or tooling.
• Experience with distributed training, model compression, or serving at scale.
• Knowledge of how to integrate ML systems into user-facing applications or APIs.
• Interest in the biology/pharma space (not required, but you’ll pick it up fast here!).

Our Perks

🧬  Every employee is a co-owner of Helical — you’ll join as part of the founding team. 🚀Operate at the cutting edge of AI — from foundational research to real deployment.

🤖Access to world-class compute infrastructure (via our supercomputing partner luxProvide, part of NVIDIA Inception).

💻Collaborate with a global network of top-tier AI researchers and engineers.

Locations

Helical is headquartered in Luxembourg and London.

This role requires alignment with one of our two core locations. We’re flexible on hybrid vs. in-office setup