• Lead Engineering Projects: Manage engineering aspects of research projects, covering data pipelines, database management, codebase development, analysis pipelines, and reporting.
• Collaborate Across Teams: Work closely with Core ML and Engineering teams to integrate and optimize large-scale ML models.
• Standardization & Best Practices: Align with engineering leads to enhance standardization and methodological practices.
• Develop Robust Software Solutions: Ensure high-quality, modular, and well-documented code that integrates smoothly with CI systems.
• Deploy ML Models: Implement models across distributed computing infrastructures, including cloud-based platforms.
• Manage Biological Data: Optimize processes for handling complex, multi-modal biological data through advanced database systems.
• Contribute to Research Initiatives: Participate in research projects, publish results, and engage in open-source contributions.
• Report & Present Findings: Clearly communicate experimental results and research findings, both internally and externally.
• Educational Background: Master’s degree in Computational Science, Machine Learning, or a related field.
• Deep Learning Experience: Proficiency in frameworks like PyTorch, TensorFlow, and Jax.
• Software Engineering Skills: Strong background in object-oriented programming, unit testing, profiling, CI, and Docker.
• Communication & Collaboration: Excellent communication skills and a collaborative mindset.