Operate and monitor ML/AI models and agentic systems in production. Build AI observability, logging, tracing, and evaluation pipelines. Monitor LLM outputs, detect drift and model degradation, and maintain data/feature pipelines. Develop CI/CD, model versioning, experiment tracking, and automate alerts and incident remediation while collaborating with data scientists and platform teams.
Key Responsibilities AI/ML Model Operations
- Deploy, manage, and monitor machine learning and AI models in production environments.
- Implement model performance monitoring including accuracy, latency, and inference metrics.
- Detect and mitigate concept drift, data drift, and model degradation.
AI Observability
- Design and implement AI observability frameworks to track model behavior and reliability.
- Monitor LLM outputs, hallucination rates, and response quality.
- Implement logging, tracing, and evaluation pipelines for AI systems.
Agentic Systems Monitoring
- Monitor agent-based AI workflows and autonomous systems.
- Track agent actions, tool usage, decision paths, and execution outcomes.
- Implement guardrails, safety monitoring, and failure detection for AI agents.
Data Pipeline Monitoring
- Monitor and maintain data ingestion, transformation, and feature pipelines.
- Ensure data quality, schema consistency, and pipeline reliability.
- Detect and resolve pipeline failures and anomalies.
Infrastructure & Automation
- Build and maintain CI/CD pipelines for ML models and AI systems.
- Manage model versioning, experiment tracking, and reproducibility.
- Automate monitoring alerts, incident response, and remediation.
Collaboration
- Work closely with data scientists, ML engineers, platform teams, and product teams.
- Support continuous improvement of AI system reliability and governance
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Compensation, Benefits and Duration
Minimum Compensation: USD 50,000
Maximum Compensation: USD 177,000
Compensation is based on actual experience and qualifications of the candidate. The above is a reasonable and a good faith estimate for the role.
Medical, vision, and dental benefits, 401k retirement plan, variable pay/incentives, paid time off, and paid holidays are available for full time employees.
This position is not available for independent contractors
No applications will be considered if received more than 120 days after the date of this post
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
