Machine Learning Engineer
1 month ago
About the Role
Join our leading-edge machine learning team as a Research Engineer, and play a pivotal role in pioneering machine learning solutions for genetic data interpretation. Our team is a technically proficient Research Engineering team who can handle high computational complexity. This role requires significant expertise in model optimization, computational efficiency, and engineering fundamentals to support a DNA-based model infrastructure.
Responsibilities:
- Improve data loading and storage efficiency for high-volume datasets
- Manage large-scale genetic models
- Optimize multi-GPU performance
- Identify and resolve bottlenecks affecting model training and inference speeds
- Develop standards for software engineering practices within the team
- Collaborate on genetic target prediction by integrating human genetics and disease data
Requirements
- Experience running large models on extensive compute resources
- Proficiency in optimizing multi-GPU training and handling bottlenecks in high-complexity systems
- Deep understanding of computational complexity and efficiency in data engineering, particularly with terabyte-scale datasets
- Familiarity with tools like OpenVINO and ONNX for inference optimization
- Strong grasp of foundational engineering principles and software engineering best practices for maintaining scalable, efficient code
Key Technical Experiences:
- Multi-GPU optimization and troubleshooting
- Practical experience with fine-tuning and pre-training large language models or similar
- Ability to manage large data pipelines (terabyte scale) and enhance model responsiveness
- Skilled in handling data models directly, not NLP-focused LLMs
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