Staff Research Engineer, AI Engineering, Science
Skills
- Expertise in deep learning on large-scale GPU clusters with distributed training techniques.
- Experience with experiment tracking and reproducibility in deep learning workflows.
- Proficient in Python ML libraries such as PyTorch, JAX, TensorFlow, NumPy, Pandas, Scikit-learn.
- Familiarity with distributed computing frameworks like PyTorch Lightning, Deepspeed, RayScale.
- Strong software engineering practices in production environments.
- Ability to balance research exploration with robust engineering.
Responsibilities
- Iterate on, optimize, deploy, and maintain innovative machine learning models and software tools for biological analysis.
- Collaborate with cross-functional teams to improve system performance based on user feedback.
- Build robust data loader pipelines for scalable distributed training and evaluation.
- Interface with product and engineering teams to adapt models for multiple use cases.
- Develop model evaluation and interpretability frameworks to aid biological insights.
- Create reusable engineering utilities to accelerate research experimentation.
- Optimize model architectures for performance, accuracy, and resource efficiency.
Education
- Master’s degree in computer science focusing on machine learning or data analytics, or equivalent industry experience.
Benefits
- Generous employer match on employee 401(k) contributions.
- Annual benefit for housing, student loan repayment, childcare, commuter costs, or other life needs.
- Life of Service Gifts to support causes important to employees.
- Paid time off for volunteering.
- Funding for select family-forming benefits.
- Relocation support to the Bay Area.
- Additional comprehensive benefits.
Average salary estimate
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