Hiring: Machine Learning Engineer, Assistant Quality Company: Glean Location: San Francisco, CA Job Posted Time: 2026-09-16 16:58:44 Employment Type: Hybrid Target Skills & Keywords : C++, Embedded Systems, GDPR, GitHub, Java, LLM, Machine Learning, NLP, Python, RAG, Reinforcement Learning, SaaS, ServiceNow, Zendesk, Zoom About the job Experience: •2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership. Required Skills: •Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows. •Design evaluation, benchmarking, and monitoring loops to measure assistant quality, model quality, and end-to-end system performance. •Develop and iterate on signals, prompts, workflows, and model-driven logic that improve reasoning, planning, personalization, and task completion quality. •Work across areas such as RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration where they materially improve product outcomes. •Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly. •Contribute to the data and ML infrastructure needed to support robust experimentation, offline and online evaluation, and continuous model improvement. Qualifications: •Strong hands-on coding ability and a track record of shipping production systems, not just prototypes or research projects. •Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration. •Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++. •A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer. •A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment. •This role is hybrid (4 days a week in our San Francisco office) Compensation: •$180,000 - $205,000 / year •Competitive benefits and rewards package •Certain roles may be eligible for variable compensation, equity, and benefits Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!