AI Infrastructure Engineer

Bright Vision Technologies • Orlando, FL

2d • $100,000 - $150,000 • Remote

About The Position

Bright Vision Technologies is seeking an AI Performance Optimization Engineer to improve throughput, latency, and cost across training and inference workloads for large neural network systems. The position spans low-level kernel optimization through distributed-system tuning and calls for expertise in GPU architecture, model parallelism, memory management, and compiler-level optimization. The successful candidate will have demonstrated production impact on AI workloads and use instrumentation and measurement to make rigorous, data-driven optimization decisions.

The engineer will collaborate with product, design, engineering, operations, and business stakeholders to turn ambiguous requirements into well-engineered solutions. The role also includes contributing to code and design reviews and mentoring more junior engineers. Bright Vision Technologies describes itself as a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States, and notes career growth potential at the organization.

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.
• Strong engineering discipline 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 for AI training and inference workloads.
• Tune AI systems across the stack, including low-level kernels and distributed systems.
• Use instrumentation and measurement to guide performance optimization decisions.
• Collaborate with product, design, engineering, operations, and business stakeholders to translate requirements into engineered solutions.
• Contribute to code reviews and design reviews.
• Mentor more junior engineers.

What This Job Offers

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