Research Engineer – Machine Learning Systems
Granica · San Francisco Bay Area · 3 wk ago
On-siteEngineeringFull-time
What You'll Work On
- Build scalable training, evaluation, and inference pipelines for machine learning systems.
- Implement and optimize algorithms for structured and tabular data.
- Develop benchmarks, datasets, and evaluation frameworks for new research ideas.
- Improve training efficiency, memory usage, and inference performance.
- Prototype new ML systems and rapidly validate research ideas.
- Collaborate closely with Prof. Andrea Montanari and Granica's research team to translate research into production systems.
What We're Looking For
- BS, MS, or PhD in Computer Science, Machine Learning, Mathematics, or a related field.
- Strong software engineering and machine learning fundamentals.
- Experience building production ML systems or ML infrastructure.
- Hands-on experience with PyTorch or JAX.
- Strong programming skills in Python.
- Experience developing evaluation frameworks, ML pipelines, or distributed systems.
- Able to translate research ideas into reliable, production-quality software.
- Experience with representation learning, structured or tabular data, probabilistic modeling, distributed training, or ML systems optimization is particularly relevant.
- Bonus: Experience working closely with research teams, experience optimizing training or inference at scale, experience with CUDA, C++, or Rust, contributions to open-source ML systems, publications or research experience in machine learning.
Compensation & Benefits
- Competitive salary, meaningful equity, and performance bonus for top performers.
- 401(k) with company match, comprehensive health coverage, and unlimited PTO.
- Daily catered meals in our Mountain View office.
- Support for research, publication, and conference participation.