Senior Machine Learning Engineer, Deep Genomics

• 3+ years of experience working as an ML Engineer, Software Engineer, or similar technical role focused on ML systems
• Hands-on experience with ML frameworks, such as PyTorch, TensorFlow, or JAX
• Proficient in Python, with a strong grasp of software architecture, design patterns, and a deep understanding of engineering best practices
• Experience with containerization and orchestration tools, such as Docker and Kubernetes
• Ability to mentor and elevate other team members' skills

Desirable

• As a Senior ML Engineer, you bring deep expertise in building robust production-grade machine learning systems and infrastructure
• You’ll lead the design, development and maintenance of core components of our AI platform – spanning training pipelines, scalable inference, evaluation frameworks, experiment tracking and reproducible tooling
• Collaborating closely with teams across engineering, machine learning, and biology, you’ll help push the boundaries of drug discovery through thoughtfully engineered systems
• Build and scale ML workflows: Collaborate closely with ML scientists and data scientists to design, implement and maintain reliable systems for model training, evaluation, and inference
• Enable experiment tracking and reproducibility: Integrate model development workflows with tools such as Weights & Biases
• Engineer robust data pipelines: Develop and maintain data ingestion and processing pipelines for scalability, reproducibility, reliability
• Prototype and iterate quickly: Partner with stakeholders to rapidly develop proof-of-concepts
• Promote software engineering best practices: Drive high standards in code quality, modular design, testing and CI/CD