AI Infrastructure Performance Engineer (C++ / Python / Rust)
About the Role
A high-impact AI initiative is seeking experienced performance engineers to contribute to advanced large-scale AI infrastructure and model optimization efforts. The role focuses on systems-level efficiency, runtime performance, and low-level optimization across modern AI training and inference environments.
This opportunity is ideal for individuals with strong systems programming backgrounds who thrive in technically demanding environments and can communicate complex engineering concepts with clarity. Candidates with experience improving production performance metrics and working across multiple programming ecosystems will be especially well aligned.
The work involves designing and evaluating performance-focused engineering tasks, improving optimization methodologies, and collaborating with technical experts to support scalable AI workloads where precision, reliability, and execution quality are critical.
What You'll Do
- Drive systems-level optimization initiatives across AI training and inference environments
- Design technically rigorous performance engineering tasks and structured solution frameworks
- Analyze runtime behavior, memory usage, latency, and throughput bottlenecks
- Evaluate engineering solutions and provide detailed technical feedback
- Develop evaluation rubrics for systems design and optimization quality
- Collaborate with cross-functional technical specialists to maintain consistency and accuracy
- Support compiler, runtime, and infrastructure performance improvement efforts
- Document optimization strategies and engineering decision-making clearly
Requirements
- 2+ years of professional experience in performance engineering, systems programming, or low-level optimization
- Strong hands-on expertise in at least one of the following: C++, Python, or Rust
- Working familiarity with multiple systems programming languages preferred
- Demonstrated experience improving production system performance metrics
- Understanding of runtime optimization, memory management, concurrency, or compiler behavior
- Ability to work consistently during weekday schedules for 30–40 hours per week
- Strong written communication and technical explanation skills
- Experience reviewing technical implementations and providing engineering feedback
- Ability to operate effectively in distributed remote engineering environments
- Preferred: Exposure to AI infrastructure, LLM systems, benchmarking, or high-performance computing workloads
- Preferred: Familiarity with evaluation frameworks, technical documentation, or structured quality assessment systems