2 months ago
Base Salary
$180k - $205k/yr
Responsibilities
- Build and improve ML and LLM-powered systems for Glean’s AI Assistant and autonomous agents.
- Design evaluation, benchmarking, and monitoring loops for assistant quality, model quality, and end-to-end performance.
- Develop signals, prompts, workflows, and model-driven logic for reasoning, planning, personalization, and task completion.
- Work on RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration as needed for product outcomes.
- Partner with product, design, and engineering teams to understand customer pain points and ship production systems.
- Contribute to data and ML infrastructure supporting experimentation, offline and online evaluation, and continuous model improvement.
Requirements
- At least two years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership.
- Strong hands-on coding ability and a track record of shipping production systems.
- Experience with one or more of LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization.
- Comfort working across modeling and product engineering, including experimentation, quality measurement, and production iteration.
- Proficiency in common ML tooling and strong software engineering fundamentals in Python, Go, Java, or C++.
- Pragmatic, product-minded approach and ability to select simple, reliable systems when appropriate.
- Proactive, low-ego working style and enthusiasm for learning in a high-velocity environment.
Benefits
- Hybrid work arrangement with four days per week in the San Francisco office.
- Medical, vision, and dental coverage.
- Generous time-off policy and 401k contribution opportunity.
- Home office improvement stipend.
- Annual education and wellness stipends.
- Regular company events and healthy lunches daily.
Categories
About Glean
Glean.ai is Intelligent AP. We leverage untapped invoice data to surface relevant context, actionable insights, and savings recommendations that power great spend decisions.