7 months ago
San Mateo, CA, USAStaff+
Base Salary
$210k - $250k/yr
Responsibilities
- Collaborate with product, data, and engineering teams to define, design, and integrate AI features into the user experience.
- Build and maintain scalable ML pipelines and infrastructure with attention to speed, flexibility, security, and scalability.
- Build and optimize LLM-powered natural-language query generation, data summarization, and data-exploration features.
- Design prompt-engineering strategies and evaluation frameworks and iterate on model performance.
- Fine-tune LLMs or custom architectures for performance, latency, and cost efficiency.
- Monitor AI research and apply state-of-the-art techniques to business problems.
Requirements
- At least 5 years of professional software engineering experience focused on machine learning or AI.
- Strong proficiency in Python and familiarity with NumPy, Pandas, and Scikit-learn.
- Experience with prompt engineering, evaluation frameworks, and hardening and productionizing GenAI applications.
- Experience designing or consuming APIs and deploying applications with Docker and Kubernetes.
- English proficiency at C1 level for technical calls and clear written communication.
- Bachelor's degree or equivalent real-world experience in Computer Science, Mathematics, or a related field.
- Preferred experience building or integrating with SaaS platforms, engineering analytics or developer-productivity tooling, ML/AI development pipelines, and coding agents.
Benefits
- Full-time role based in San Mateo, CA, with the team meeting in person several days per week.
Tech Stack
Categories
About Faros
Faros builds an engineering intelligence and observability platform that unifies data from code, people, and systems to measure and manage software delivery and AI impact. It sells a SaaS platform to engineering leaders with enforceable workflows, policy, and custom metrics across the software development lifecycle. Founded in 2019 and headquartered in the San Francisco Bay Area, it serves customers from high-growth tech companies to Fortune 500 enterprises.