Machine Learning Engineer

UST is looking for a Machine Learning Engineer (ML Engineer II) to help build and optimize multi-agent workloads end-to-end, from application behavior down to inference runtime and accelerator hardware. This onsite role in Oregon supports engineers who want to translate agentic AI into measurable performance improvements across latency, throughput, and resource utilization.

What you’ll do

• Develop a multi-agent workload at the application level, then profile and optimize execution all the way down to inference runtime, OMIX/middleware, compute runtime, Linux GPU driver, and accelerator hardware.
• Optimize for latency, throughput, tokens/sec, memory footprint, and accelerator utilization.
• Select and tune models and inference engines based on agent workload characteristics, hardware capabilities, and performance requirements.

Core qualifications

• Hands-on development of multi-agent workloads.
• Experience with agent frameworks including LangGraph/LangChain, AutoGen, CrewAI, or similar.
• Strong understanding of LLMs, SLMs, and multimodal models, including Transformer architecture, attention mechanisms, tokenization, context windows, and KV cache.
• Hands-on experience with model selection, evaluation, and deployment for different agentic workload requirements.
• Understanding of model formats and optimization, including ONNX, Open VINO IR, safe tensors, and quantization such as FP16, BF16, INT8, and INT4.
• Experience with inference engines/runtime frameworks such as Open VINO, ONNX Runtime, vLLM, llama.cpp, or TGI.
• Understanding of prefill vs. decode, batching, continuous batching, speculative decoding, KV-cache management, and memory optimization.
• Working knowledge of CPU/GPU execution, device placement, and heterogeneous inference.
• Ability to benchmark and compare models, inference engines, and runtime configurations to identify performance bottlenecks.
• Understanding of GPU memory, kernel execution, synchronization, device selection, and host/device data movement.
• Familiarity with middleware and accelerator compute runtimes such as OMIX/OneAPI/SYCL, Level Zero, or OpenCL.
• Strong Python and working knowledge of C/C++.
• Git/GitHub, Linux shell, and debugging tools.
• Practical use of GitHub Copilot for development, debugging, and code generation.
• Docker/container fundamentals.
• Ability to benchmark and profile AI workloads and analyze whether performance issues originate in the agent, model, inference engine, runtime, or driver.

Technologies you may work with

• LangGraph, LangChain, AutoGen, CrewAI
• Python, C/C++, Linux, Git, GitHub, GitHub Copilot, Docker
• ONNX, Open VINO IR, safe tensors, FP16, BF16, INT8, INT4
• Open VINO, ONNX Runtime, vLLM, llama.cpp, TGI
• OMIX, OneAPI, SYCL, Level Zero, OpenCL

Compensation and benefits

Compensation range: USD 82,000 to 123,000 per year.

• Full-time employees accrue minimum 10 days of paid vacation per year.
• 6 days of paid sick leave each year (pro-rated for new hires throughout the year).
• 10 paid holidays.
• Eligible for paid bereavement leave and jury duty.
• Eligible to participate in the 401(k) Retirement Plan with employer matching.
• Medical, dental, and vision insurance for employees and their dependents residing in the US.
• Company-paid Employee Only benefits: basic life insurance, accidental death and disability insurance, and short- and long-term disability benefits.
• Regular employees may purchase additional voluntary short-term disability benefits.
• Eligible to participate in a Health Savings Account (HSA).
• Eligible to participate in a Flexible Spending Account (FSA) for healthcare, dependent child care, and/or commuting expenses.