ML Systems Engineer: GPU-Accelerated Training & Inference

voltai-com; Edison (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Unlimited PTO

Comprehensive Health Coverage

Free Meals and Snacks

Professional Growth

Visa Sponsorship

Job summary

Voltai is hiring in California to build and optimize high-performance ML pipelines and inference systems for LLMs in enterprise environments. You will design CUDA kernels, implement low-precision techniques, and Architect distributed training across multiple GPUs and nodes.

The role emphasizes production-ready research translate, collaboration with researchers and infra teams, and tuning for real-world hardware deployments in a fast-paced startup setting.

Qualifications

• Expertise in systems-level programming for ML workloads.
• Experience optimizing transformer kernels and GPU throughput.
• Proficiency with GPU-accelerated inference frameworks.
• Ability to translate research to production-grade systems.
• Strong performance monitoring and bottleneck analysis.

Responsibilities

• Design and maintain high-performance ML pipelines for training, evaluation, and inference of LLMs and retrieval-augmented systems, with a focus on hardware efficiency and throughput
• Optimize core transformer operations at the kernel level, designing and tuning custom kernels and low-level implementations for GPU-accelerated workloads
• Implement and integrate low-precision computation techniques to reduce memory footprint and accelerate inference with minimal accuracy degradation
• Build and maintain inference engines for on premises deployments
• Architect distributed training and inference systems
• Collaborate closely with researchers and infra teams to bring cutting-edge model innovations into production
• Interface directly with enterprise hardware environments, tuning performance based on real-world deployment constraints

Skills

C/C++/Rust

CUDA kernel design

Low-precision compute

Inference systems

Distributed training

Research to production

Performance monitoring

Tools

CUDA

vLLM

SGLang

TensorRT

GGUF/GGML

Job description

Voltai is hiring in California to build and optimize high-performance ML pipelines and inference systems for LLMs in enterprise environments. You will design CUDA kernels, implement low-precision techniques, and Architect distributed training across multiple GPUs and nodes.

The role emphasizes production-ready research translate, collaboration with researchers and infra teams, and tuning for real-world hardware deployments in a fast-paced startup setting.