AI Performance Engineer

Bright Vision Technologies • Aurora, IL

3d • $75,000 - $100,000 • Remote

About The Position

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. The AI Performance Engineer will focus on maximizing throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems. The role spans low-level kernel optimization through distributed system tuning and requires understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization. The engineer will apply instrumentation and measurement to make rigorous, data-driven optimization decisions for production AI workloads.

The role involves working closely with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into well-engineered solutions. The engineer will contribute to code and design reviews and mentor more junior engineers. The position is full-time, direct W2, and 100% remote within the United States. The annual salary range is $75,000–$100,000. Bright Vision Technologies cannot sponsor new H-1B visa petitions; U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are encouraged to apply.

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.
• Demonstrated impact on production AI workloads and a track record of shipping meaningful work that performs reliably in production.

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 throughput, latency, and cost across training and inference workloads for large neural network systems.
• Work across low-level kernel optimization and distributed system tuning.
• Use instrumentation and measurement to guide data-driven optimization decisions for production AI workloads.
• Collaborate with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into well-engineered solutions.
• Participate in code reviews and design reviews.
• Mentor more junior engineers.

What This Job Offers

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