[Remote] AI Performance Engineer

Note: The job is a remote job and is open to candidates in USA. 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 optimize throughput, latency, and cost for large-scale neural network training and inference workloads across GPUs, distributed systems, memory management, and compiler-level optimization. The role also involves cross-functional collaboration, code and design reviews, and mentoring junior engineers.

Responsibilities

• We are seeking an AI Performance Engineer to focus on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems
• The role spans the full stack from low-level kernel optimization to distributed system tuning, requiring deep understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization
• In this role you will work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions, and will be expected to raise the bar through code review, design review, and mentorship of more junior engineers
• The successful candidate brings strong engineering discipline, a clear communication style, and a track record of shipping meaningful work that holds up well in production

Skills

• 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
• 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

Benefits

• 100% Remote (U.S.)
• Full-time, Direct W2

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