Job Description: Join an AI-native biotechnology company at the forefront of transforming cancer treatment and systems biology. This role offers the chance to work in a nimble, innovative environment with a highly technical interdisciplinary team. You will design and build systems for scalable, distributed training and inference of machine learning models, specifically custom vision transformers developed in-house. Collaborating with the ML and Engineering teams, you'll optimize systems for research iteration and scaling while solving complex, impactful challenges.

Key Responsibilities:

• Design and build systems for distributed training and inference of custom ML models.
• Collaborate with ML and Engineering teams to develop and scale ML platforms.
• Optimize data loaders and model architectures for performance.
• Develop solutions for scalable model result analysis.

Qualifications:

• 2+ years of experience in building systems for distributed ML training and inference (using GPUs, AWS, etc.).
• Strong proficiency with PyTorch and experience in ML model and data loader development.
• Familiarity with modern frameworks like Ray, PyTorch Lightning, and Huggingface Accelerate.
• Problem-solving mindset with an adaptable and collaborative approach.

Perks:

• Remote-first computational work with opportunities for travel to San Francisco.
• Onsite lunch, sponsored travel, and offsite summits.
• Generous health, dental, and vision insurance; flexible time off; parental leave; and more.

This is an exciting opportunity to make an impact in the biotech industry and contribute to groundbreaking therapies.