Architect and execute large-scale custom model training and fine-tuning jobs on multi-node, multi-GPU clusters
Optimize training throughput and memory efficiency using distributed training strategies and mixed-precision techniques
Design and develop autonomous AI Agents capable of multi-step reasoning and planning to automate complex manufacturing workflows
Analyze and profile complex workloads to identify bottlenecks in compute, memory bandwidth, and latency
Write and optimize high-performance kernels using CUDA, HIP, or custom assembly to unlock hardware capabilities
Collaborate with Hardware Architects to define features for next-generation GPUs
Design and implement performance regression testing suites
Mentor junior engineers on parallel programming paradigms and optimization techniques

Technical Degree required
Ph.D. in Computer Science or Statistics background highly desired
Deep understanding of GPU architecture and experience managing GPU resources in cloud and on-prem environments
Hands-on experience with Distributed Data Parallel, Fully Sharded Data Parallel, and model parallelism techniques
Proficiency in fine-tuning Large Language Models using PEFT techniques and optimizing inference engines
Experience developing GenAI applications and AI Agents using frameworks like LangChain, LangGraph, LlamaIndex, or AutoGen
Proficiency with Large Language Models, including prompt engineering and Chain-of-Thought reasoning
Experience in building and executing end-to-end ML systems automating training, testing and deploying Machine Learning models
Familiarity with machine learning frameworks (PyTorch required, TensorFlow, scikit-learn, etc.)
Software development skills and the desire to work on cutting edge development in a Cloud environment
Strong scripting and programming skills in Python or Java (Python preferred)
Experience with CI/CD tools (Jenkins, Git, Docker, Kubernetes)
5+ years of experience in performance optimization, parallel computing, or low-level systems programming
Deep expertise in C++ and at least one GPGPU framework (CUDA preferred, but HIP/OpenCL/Metal are acceptable)
Outstanding analytical thinking, interpersonal, oral and written communication skills
Ability to prioritize and meet critical project timelines in a fast-paced environment

MTS, AI Engineering, SMAI

Key skills