Research Systems Engineer
San Francisco, CA · Full-time · On-site
Overview
As a Research Systems Engineer, you will bridge the gap between research and production. You'll build the infrastructure that enables our research team to rapidly prototype, experiment, and deploy optimization algorithms at scale.
What You'll Do
Design and build experimentation infrastructure for ML optimization research
Create scalable pipelines for running optimization experiments across diverse agent systems
Develop tooling for experiment tracking, reproducibility, and analysis
Optimize system performance for large-scale optimization runs
Work with researchers to productionize successful algorithms
Build monitoring and observability for research infrastructure
What We Look For
Strong software engineering skills with experience in distributed systems
Experience building infrastructure for ML research or experimentation
Proficiency in Python and experience with ML frameworks
Familiarity with cloud platforms (AWS, GCP) and containerization
Strong debugging and optimization skills
Nice to Have
Experience with ML experiment tracking tools (Weights & Biases, MLflow, etc.)
Background in HPC or scientific computing
Experience scaling systems to handle large workloads
Familiarity with RL training infrastructure
About Lucidic AI
We build tooling that automatically evaluates and improves enterprise AI agents using search + learning loops across prompts, tools, and policies. Our customers care about reliability, auditability, and measurable gains.
