AI Optimization Engineer

Bright Vision Technologies • Artesia, CA

1d • $100,000 - $100,000 • Remote

About The Position

Bright Vision Technologies is seeking an AI Optimization Engineer to improve throughput, reduce latency, and lower costs across training and inference workloads for large neural network systems. The role covers work from low-level kernel optimization through distributed system tuning, requiring expertise in GPU architecture, model parallelism, memory management, and compiler-level optimization. The engineer will use strong instrumentation and measurement practices to make rigorous, data-driven optimization decisions for production AI workloads.

The engineer will collaborate with product, design, engineering, operations, and business stakeholders to turn ambiguous requirements into well-engineered solutions. The role also involves raising engineering standards through code and design reviews and mentoring more junior engineers. The successful candidate will bring engineering discipline, clear communication, and a track record of delivering reliable production work.

This is a full-time, direct W2 position, performed 100% remotely within the United States. The listed salary is $100,000 annually. Bright Vision Technologies cannot sponsor new H-1B visa petitions for this position; U.S. citizens, Green Card holders, EAD holders, and candidates transferring an H-1B 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.

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 costs across training and inference workloads for large neural network systems.
• Optimize deep learning workloads on modern GPUs, spanning low-level kernels and distributed system tuning.
• Apply instrumentation and measurement to guide data-driven optimization decisions.
• Collaborate with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into solutions.
• Participate in code reviews and design reviews to raise engineering standards.
• Mentor more junior engineers.
• Deliver meaningful work that is reliable in production.

What This Job Offers

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