Staff/Senior Machine Learning Research Engineer, Intelligent Systems

Job summary

Responsibilities

As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter.

• Move across AIS’s core problem areas as needed — training/fine-tuning, inference, memory and retrieval, evaluation and observability, orchestration and tool-use infrastructure…
• Research and prototype novel methods for agent performance improvement in a production/enterprise-ready setting — continuous learning loops, automated curriculum or data…
• Build AI agents and internal tooling that reduce bottlenecks in AIS’s own processes — cutting down time spent on repetitive evaluation, data, or experimentation work so teams can…
• Partner with other ML engineers, software engineers, product managers, customers, data annotators, and Forward Deployed Engineers to take your work from idea to production and…
• Set AI/ML technical direction, mentor senior and staff-track engineers and scientists across teams, and raise the bar on experimental rigor org-wide

What they're looking for

• 5+ years of experience as an ML engineer or applied/research scientist, including direct experience training or fine-tuning models in production systems
• PhD in Computer Science, Electrical Engineering, or a related field
• Broad, hands-on fluency across the agentic ML stack — model training and fine-tuning (SFT, RLHF/RLAIF, reward modeling), evaluation and observability infrastructure, and agent…
• Demonstrated ability to move across problem areas rather than specialize in one corner of the ML stack — comfortable picking up unfamiliar parts of a system quickly
• Track record of partnering with software engineers to productionize research and experimental work, not just deliver a one-off analysis — and of pushing code to production…