[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, spanning GPU kernels, distributed systems, memory management, and compiler 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
- * 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
Company Overview