Staff/Senior Machine Learning Research Engineer, Intelligent Systems

Summary by AIEngineer.careers

Staff/Senior Machine Learning Research Engineer, Intelligent Systems is a Machine Learning Research Engineer role (full-time). with Scale AI, Inc. in SAN FRANCISCO, US. Compensation shown: $265K–$331K. Imported listing (source: justjobs.com). Apply on the employer's site (justjobs.com).

Imported listing (source: justjobs.com) · Apply on justjobs.com

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SAN FRANCISCO · US

$265K–$331K

Full-time

STAFF

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Imported job description

Sourced from justjobs.com

Scale AI's Applied Intelligence Systems team is hiring a Staff/Senior Machine Learning Research Engineer to advance production-grade agentic AI across enterprise and government use cases. The role spans training and fine-tuning, evaluation and observability, orchestration and tool-use infrastructure, and applied research on new agent capabilities. You will write code and ship production systems while setting AI/ML technical direction across the team.

Responsibilities

Research and prototype novel methods to improve agent performance, including continuous learning loops, automated data generation, and online/offline RL
Build AI agents and internal tooling to reduce bottlenecks in evaluation, data, and experimentation workflows
Partner with ML engineers, software engineers, product managers, and Forward Deployed Engineers to move work from idea to production
Set AI/ML technical direction and mentor senior and staff-track engineers and scientists across teams

Requirements

5+ years as an ML engineer or applied/research scientist, including training or fine-tuning models in production systems
PhD in Computer Science, Electrical Engineering, or a related field
Hands-on fluency across the agentic ML stack: model training and fine-tuning (SFT, RLHF/RLAIF, reward modeling), evaluation and observability, and agent architecture
Demonstrated ability to move across problem areas and pick up unfamiliar systems quickly
Track record of productionizing research and setting technical direction adopted by other teams

Nice to Have

Published research, open-source contributions, or patents in agent training, LLM alignment, or applied ML
Experience with online learning, continuous fine-tuning, or automated curriculum generation from production traces
Experience with model or systems optimization for training efficiency, latency, cost, or inference at scale
Experience in regulated or enterprise/government contexts
Prior technical lead experience across multiple teams or problem areas

Benefits

Health insurancedental insurancevision insuranceretirement planlearning stipendptocommuter stipendEquity / stock options

Tech Stack

Agent ArchitecturesEvaluation SystemsFine-tuningLLMPyTorchReinforcement LearningRLAIFRLHF

Scale AI, Inc.

San Francisco · US · 5925+ employees

Scale AI is a leading data infrastructure company that provides comprehensive solutions for training, evaluating, and deploying machine learning models. It supports organizations across various industries, including government and enterprise, by combining human-in-the-loop data labeling with model evaluation and safety alignment.