Remote AI Performance Optimization Engineer

Bright Vision Technologies; Monroe (NJ); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an AI Performance Optimization Engineer to maximize throughput, minimize latency, and reduce costs across training and inference workloads for large neural networks. You will work from kernel optimization to distributed systems, with deep expertise in GPU architectures, model parallelism, memory management, and compiler optimization.

Collaboration across product, design, and operations is essential to drive measurable production gains.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field.
• Six+ years of experience in performance engineering, ML systems, or HPC.
• 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.
• Understanding of memory hierarchies, communication primitives, and parallelism strategies.
• Strong measurement, debugging, and analytical reasoning skills.
• Excellent communication and collaboration skills.

Responsibilities

• Profile and optimize end-to-end AI training and inference pipelines for throughput, latency, and cost.
• Identify and eliminate bottlenecks across data loading, model compute, communication, and memory.
• Implement and tune quantization, sparsity, and pruning strategies to reduce model footprint and accelerate inference.
• Optimize distributed training using tensor parallelism, pipeline parallelism, FSDP, and ZeRO-style sharding.
• Tune attention implementations using FlashAttention, paged attention, and related techniques.
• Implement KV cache optimization, continuous batching, and speculative decoding for LLM serving.
• Drive compiler-level optimizations using Triton, XLA, TorchInductor, or TVM, working with the broader ML framework community to land improvements that translate into measurable end-to-end performance gains.
• Optimize data pipelines, sharding strategies, and storage access patterns for high-throughput training.
• Build and maintain rigorous benchmark suites and regression frameworks across workloads.
• Collaborate with ML and platform engineering teams to embed best practices in standard pipelines.
• Drive cost-efficiency improvements through model architecture, hardware selection, and scheduling strategies.
• Evaluate new hardware and software offerings, and advise on adoption.
• Document performance tuning playbooks and share findings broadly across engineering teams.
• Stay current with AI systems research and translate advances into production improvements.

Skills

Python

C++

Performance engineering

ML systems

GPU optimization

Distributed training

Profiling tools

Model compression

Memory hierarchy

Performance debugging

Team collaboration

Education

Bachelor’s or Master’s degree in Computer Science or related field

Job description

Bright Vision Technologies is seeking an AI Performance Optimization Engineer to maximize throughput, minimize latency, and reduce costs across training and inference workloads for large neural networks. You will work from kernel optimization to distributed systems, with deep expertise in GPU architectures, model parallelism, memory management, and compiler optimization.

Collaboration across product, design, and operations is essential to drive measurable production gains.