Senior Applied Machine Learning Engineer

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Collaborating closely with our AI Function lead, you will engage across all three of our AI products: Moderate, Discover, and Respond.

• Your primary focus will be on the most challenging applied ML tasks and enhancing the foundational elements (evaluation harnesses, observability, reference implementations) that ensure AI operates seamlessly for engineers who are not specialists in ML.

• Take ownership of complex applied ML features from conception to production.

• Develop evaluation pipelines, curated datasets, and observability tools (with much of this being greenfield).

• Produce reference implementations that guide other engineers on effectively delivering AI solutions.

• Collaborate with Product and Engineering teams to bridge the gap between technical feasibility and the objectives teams are aiming to achieve.

⛳️ Requirements

• Over 5 years of experience in developing applied ML systems for production environments.

• Practical experience with LLMs, including classification, summarization, RAG, and agentic workflows.

• Strong instincts for ML evaluation: creating datasets, conducting offline and online evaluations, and defining performance metrics.

• Capability to independently manage a feature from start to finish with minimal supervision.

• Proficient in Python and comfortable working within a production codebase.

• Experience in creating internal tools or platforms that empower other engineers is a significant advantage.

🏝️ Benefits

• Competitive salary plus equity.

• Fully remote work option, with the possibility of accessing our Boulder, CO office.

• Flexible PTO, ample holiday time, and a full week off between Christmas and New Year's.

• Various healthcare options, including FSA/HSA plans.

• 401k (both traditional and Roth) with company matching, fully vested immediately.

• Comprehensive family and parental leave policy (12 weeks per year).

• Biannual team offsite events.