AI Engineer at TrustLab
Date: 1 day ago
City: San Mateo, CA
Contract type: Full time
Who we are:
TrustLab deploys cutting edge solutions to evaluate AI agents, models and apps for enterprise customers. With a 5 year track record working with large and small clients incl.social media companies and digital market places, and guided by founders who previously worked in senior leadership positions at Google, YouTube, TikTok, and Reddit, we are creating industry leading LLM based solutions for agentic system evaluation and labeling. Our approach includes human-in-the-loop and LLM-as-a-judge technologies, with a focus on rapid innovation and production level scaling. You’ll join a small, mission-driven team where your contributions have a direct impact on real-world issues.
What you’ll do:
At TrustLab, your work won’t live in theory - it will power live systems used at large scale. You’ll work as part of a team that develops, tunes, and optimizes LLM-driven solutions that interpret and reason about complex digital content, while experimenting rapidly from design to deployment and seeing immediate feedback from real-world use cases. Partnering closely with other engineers, researchers, and product leaders, you’ll develop approaches to model training and evaluation, participating from early R&D through to production launches, and ensuring your work directly shapes how millions of people experience AI-powered content.
Key Responsibilities:
TrustLab deploys cutting edge solutions to evaluate AI agents, models and apps for enterprise customers. With a 5 year track record working with large and small clients incl.social media companies and digital market places, and guided by founders who previously worked in senior leadership positions at Google, YouTube, TikTok, and Reddit, we are creating industry leading LLM based solutions for agentic system evaluation and labeling. Our approach includes human-in-the-loop and LLM-as-a-judge technologies, with a focus on rapid innovation and production level scaling. You’ll join a small, mission-driven team where your contributions have a direct impact on real-world issues.
What you’ll do:
At TrustLab, your work won’t live in theory - it will power live systems used at large scale. You’ll work as part of a team that develops, tunes, and optimizes LLM-driven solutions that interpret and reason about complex digital content, while experimenting rapidly from design to deployment and seeing immediate feedback from real-world use cases. Partnering closely with other engineers, researchers, and product leaders, you’ll develop approaches to model training and evaluation, participating from early R&D through to production launches, and ensuring your work directly shapes how millions of people experience AI-powered content.
Key Responsibilities:
- Train, evaluate, and monitor new and improved LLMs and other algorithmic models
- Test and deploy content moderation models in production, and iterate based on real-world performance metrics and feedback loops.
- Ensure results delivered to customers, pushing for change in approach where needed and be proactive in cross-functional execution.
- Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Proficiency in Python. Experience with AWS and CI/CD processes & tools is a strong plus.
- Experience with prompt-engineering techniques and familiarity with multiple LLM providers.
- industry experience in NLP / Computer Vision, or making LLM’s work in production for non-trivial use cases.
- Hands-on experience with debugging issues in production environments, especially on AWS.
- Ttrack record delivering results under time and resource pressure
- Work with a group of renown industry leaders in AI and Online Safety to shape the future of the industry.
- Ample opportunity and support for growth.
- Apply AI technology to real-world business use cases at a significant scale, with blue chip customers
- Work as part of a team where you can know everyone, but don’t have to do everyone’s job.
- Competitive compensation, comprehensive benefits, and hybrid in-office policy.
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