Remote ML Performance Engineer: AI Throughput Optimizer

Bright Vision Technologies; Maple Grove (MN); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an ML Performance Engineer to optimize AI training and inference across large neural network systems. The role spans from low-level kernel optimization to distributed system tuning, requiring deep GPU architecture knowledge and compiler-level optimization.

You will work with cross-functional partners to translate ambiguous requirements into well-engineered solutions and drive measurable end-to-end performance 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.
• 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.

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, with broader ML framework community.
• 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 across teams.
• Stay current with AI systems research and translate advances into production improvements.

Skills

Python

C++

Performance engineering

Distributed training

Profiling tools

Measurement & debugging

Education

Bachelor’s or Master’s in CS/CE or related field

Tools

Triton

XLA

TorchInductor

TVM

CUTLASS

TensorRT-LLM

Job description

Bright Vision Technologies is seeking an ML Performance Engineer to optimize AI training and inference across large neural network systems. The role spans from low-level kernel optimization to distributed system tuning, requiring deep GPU architecture knowledge and compiler-level optimization.

You will work with cross-functional partners to translate ambiguous requirements into well-engineered solutions and drive measurable end-to-end performance gains.