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 transform 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 products that advance computational chemistry.
What you'll do
- Translate novel research papers and ideas into high-performing, production-ready scientific code
- Lead ML model ideation, benchmarking, and integration into large-scale simulation frameworks
- Architect and optimize distributed training pipelines on GPU infrastructure
- Drive software through entire product lifecycle from research through launch and support
- Bridge research prototypes and product-grade implementations
- Perform hardware-level optimizations for computational chemistry workloads
What they're looking for
- Machine learning engineering and model development
- Python and scientific computing (PyTorch, TensorFlow, JAX)
- Distributed training and GPU optimization
- Software engineering best practices and productionization
- Structural biology or computational chemistry knowledge
- MLOps and cloud platforms (AWS, GCP, Azure)
- Research paper implementation and translation
- Interdisciplinary collaboration across AI and physical sciences
Benefits
- Competitive base salary with performance-based incentives and equity
- Comprehensive medical, dental, and vision coverage with employer 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 and professional development opportunities
Opens the official application on the employer’s site. No login required.
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
- Walk us through a time you translated a research paper into production software—what were the key challenges?
- Describe your experience optimizing distributed ML training pipelines. What bottlenecks did you encounter and how did you address them?