Machine Learning Research Engineer at Deep Genomics

Advance drug discovery with Deep Genomics as a Machine Learning Research Engineer in Toronto. Utilize your expertise in PyTorch and modern ML architectures to optimize research systems.

Deep Genomics seeks a research engineer who navigates academic ML research and production systems. Ideal candidates possess a strong mathematical foundation and key skills in model implementation, debugging, and balancing rapid iteration with technical debt. This role emphasizes collaboration with researchers to build core tooling that empowers innovation.

Key Responsibilities:

• Develop and maintain engineering infrastructure for rapid iteration

• Refactor and optimize experimental research code rigorously

• Implement and evaluate modern deep learning models using Py Torch

• Test and troubleshoot complex ML systems for optimal performance

• Make architectural decisions balancing research speed and technical debt

Requirements:

• Solid understanding of linear algebra, calculus, and probability

• High proficiency with PyTorch for model building

• Strong programming skills in concurrency and memory management

• Experience debugging software correctness and performance

• High tolerance for ambiguity and unstructured code

Utilize your machine learning skills to enhance Deep Genomics' impact on drug discovery and patient outcomes.
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