As a Machine Learning Engineer intern 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 various biological foundation models architectures (e.g. Transformers, SSMs).
- Optimize model performance, latency, and throughput across environments.
- Apply the latest post-training research to current architectures and data setups.
- Design modular, reusable ML components for internal and open-source use.
- Collaborate with researchers to turn notebooks into production-grade systems.
- Own ML infrastructure components (data loading, distributed compute, experiment tracking, etc.).
- Drive experimentation around fine-tuning, transfer learning, and evaluation at scale.
Machine Learning Intern in City of London employer: Helical
HeliCal is an exceptional employer that fosters a collaborative and innovative work culture, where cutting-edge research in computational biology meets real-world applications. Employees benefit from mentorship opportunities, professional growth, and the chance to work alongside industry leaders in a vibrant location that encourages creativity and scientific exploration. With a strong commitment to employee development and impactful projects, HeliCal offers a rewarding environment for those passionate about advancing drug development through machine learning.
