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 manage large-scale genetic models, optimize multi-GPU performance, and handle high computational complexity. This role requires significant expertise in model optimization, computational efficiency, and engineering fundamentals to support Roslind’s DNA-based model infrastructure.

*Core Skills:*

•⁠ ⁠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 pretraining large language models or similar

•⁠ ⁠Ability to manage large data pipelines (terabyte scale) and enhance model responsiveness

•⁠ ⁠Skilled in handling DNA/genetic data models directly, not NLP-focused LLMs

*Core Responsibilities:*

•⁠ ⁠Improve data loading and storage efficiency for high-volume datasets

•⁠ ⁠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