AI Performance Optimization Engineer
$100,000–$150,000 year
On-site · Duluth, Minnesota, United States
Job Summary
AI Performance Optimization Engineer at Bright Vision Technologies focuses on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems. The role spans from low-level kernel optimization to distributed system tuning, requiring deep understanding of GPU architecture, model parallelism, memory management, and compiler-level optimization. The ideal candidate has demonstrated impact on production AI workloads, with rigorous instrumentation and data-driven optimization decisions, and will collaborate with product, design, engineering, operations, and business stakeholders to translate ambiguous requirements into well-engineered solutions, while contributing to code reviews, design reviews, and mentorship of junior engineers.
Required Qualifications
- 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
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