Remote ML Performance Engineer - Throughput & Latency

Bright Vision Technologies; Highlands Ranch (CO); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an ML Performance Engineer to optimize large neural network workloads across training and inference on modern GPUs. The role spans from low-level kernels to distributed system tuning, with emphasis on throughput, latency, and cost efficiency in production AI pipelines.

You will collaborate with product, design, and platform teams to translate ambiguous requirements into robust, data-driven optimizations, mentor junior engineers, and document playbooks for

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.

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 the 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 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

Deep learning workloads

Education

Bachelor’s or Master’s degree in Computer Science/Computer Engineering

Tools

Triton

XLA

TorchInductor

TVM

FlashAttention

CUTLASS

TensorRT-LLM

DeepSpeed

Job description

Bright Vision Technologies is seeking an ML Performance Engineer to optimize large neural network workloads across training and inference on modern GPUs. The role spans from low-level kernels to distributed system tuning, with emphasis on throughput, latency, and cost efficiency in production AI pipelines.

You will collaborate with product, design, and platform teams to translate ambiguous requirements into robust, data-driven optimizations, mentor junior engineers, and document playbooks for