SandboxAQ
ML Research Engineer, AI for Life Sciences
United States (Remote)$134.4k–$252kfulltimemidAdded today
About this role
SandboxAQ seeks an ML Research Engineer to translate cutting-edge AI research into production-grade software for drug and materials discovery. You'll architect and optimize scientific codebases, scale distributed training pipelines on GPU infrastructure, and drive prototypes into robust, commercially-viable products in computational chemistry.
What you'll do
- Translate research papers and novel ideas into high-performing, production-ready scientific code
- Lead ML model development, benchmarking, and dataset curation for large-scale simulation frameworks
- Architect and optimize distributed training pipelines on GPU infrastructure
- Drive software through complete product lifecycle from research through launch and long-term support
- Perform hardware-level optimizations to advance computational chemistry capabilities
- Bridge research prototypes and commercial product requirements
What they're looking for
- Machine learning engineering and model optimization
- Python and scientific computing (PyTorch, TensorFlow, or similar)
- Distributed systems and GPU-accelerated computing
- Structural biology and computational chemistry fundamentals
- Software architecture and productionization best practices
- MLOps and cloud platform deployment
- Research paper implementation and translation
- Collaborative work across interdisciplinary teams
Benefits
- Comprehensive medical, dental, and vision coverage with employer premium contributions
- Retirement savings with company matching
- Paid parental leave and family-building benefits
- Flexible paid time off and company-wide seasonal breaks
- Flexible work arrangements
- Equity participation and performance-based incentives
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SandboxAQ
SandboxAQ develops GPS-independent navigation solutions and related data infrastructure technologies. The company is hiring Data Engineers and other technical roles to build and enhance data pipelines that support advanced navigation applications across various sectors.
- Website
- sandboxaq.com
Likely interview questions
- Describe your experience translating a research paper into production software. What were the key challenges in moving from prototype to robust code?
- Tell us about your experience with distributed training pipelines and GPU optimization. What scale of models have you worked with?