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 Infrastructure Engineer will optimize the performance, latency, and cost of large-scale neural network training and inference workloads across GPU, kernel, compiler, and distributed systems. The role also involves cross-functional collaboration, engineering reviews, and mentoring junior engineers.
Responsibilities
- Focus on extracting maximum throughput, minimizing latency, and reducing cost across training and inference workloads for large neural network systems
- Work closely with cross-functional partners — product, design, engineering, operations, and business stakeholders — to translate ambiguous requirements into well-engineered solutions
- Raise the bar through code review, design review, and mentorship of more junior engineers
Skills
- Bachelor's or master's degree in computer science, Computer Engineering, or 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 (United States)
- Tremendous career growth potential
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