AI Performance Engineer

Bright Vision Technologies • Schaumburg, IL

1d • $75,000 - $100,000 • Remote

About The Position

Bright Vision Technologies is seeking an AI Performance Engineer to maximize throughput, minimize latency, and reduce costs across training and inference workloads for large neural network systems. The role spans low-level kernel optimization through distributed-system tuning, with work involving GPU architecture, model parallelism, memory management, and compiler-level optimization. The engineer will apply instrumentation and rigorous measurement to make data-driven optimization decisions for production AI workloads.

The position works with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into well-engineered solutions. The engineer is also expected to contribute through code and design reviews and to mentor more junior engineers, while maintaining strong engineering discipline, clear communication, and a record of delivering production-ready work.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• Six or more years of experience in performance engineering, ML systems, or HPC.
• Strong proficiency in Python and C++.
• Hands-on experience optimizing deep learning workloads on modern GPUs.
• Deep understanding of distributed training and inference techniques.
• Experience with profiling tools across CPU, GPU, and distributed systems.
• Familiarity with model compression techniques and their accuracy implications.
• Strong grasp of memory hierarchies, communication primitives, and parallelism strategies.
• Excellent measurement, debugging, and analytical reasoning skills.
• Strong communication and collaboration skills.

Nice To Haves

• Experience optimizing LLM inference at production scale.
• Contributions to vLLM, TensorRT-LLM, DeepSpeed, or similar projects.
• Familiarity with custom kernel authoring in Triton or CUTLASS.
• Experience with FinOps for AI workloads.
• Publications or talks on AI systems performance.

Responsibilities

• Optimize training and inference workloads for throughput, latency, and cost.
• Tune AI systems across the stack, from low-level kernels to distributed systems.
• Use instrumentation and measurement to make data-driven optimization decisions.
• Work with product, design, engineering, operations, and business stakeholders to turn ambiguous requirements into well-engineered solutions.
• Participate in code and design reviews.
• Mentor more junior engineers.
• Deliver meaningful work that performs reliably in production.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior