Software Engineer, AI Research – Prototyping

• Track emerging techniques in voice AI, LLM reasoning, and agent systems, and identify which ones matter for us
• Design structured experiments with real controls: know when a result is signal and when it is noise
• Build rapid prototypes and test them against real conversation data
• Run head-to-head evaluations of models, providers, and techniques (reasoning approaches, speech models, orchestration patterns)
• Turn every investigation into a team-usable artifact: a benchmark, a written deep-dive, a tech talk, or a recommendation with evidence
• Work with platform engineers to hand off validated ideas for production implementation
• Build the internal knowledge base for how and why our AI stack works the way it does

• 3+ years of software engineering or applied ML experience
• Strong Python skills; able to build and run your own experiments end-to-end without infrastructure support
• Hands‑on experience with LLMs: prompting, evaluation, and an intuition for how model behavior changes across techniques and providers
• Experimental rigor: experience designing tests with controls, baselines, and honest measurement
• A track record of teaching or knowledge transfer in some form: teaching or TA experience, workshops, technical writing, internal tech talks, well‑documented open source, or developer education
• Intellectual honesty: comfortable reporting that a promising idea did not work.

Demonstrates expertise in Python programming and applied machine learning, with a strong focus on experimental design and knowledge transfer. Capable of building prototypes and conducting rigorous evaluations of AI models and techniques.

• Python Programming
• Applied Machine Learning
• Experimental Design
• LLM Experience
• Knowledge Transfer

• Software Engineering
• Experiment Design
• Model Evaluation
• Prototyping
• Data Analysis

• Intellectual Honesty
• Teaching Experience
• Technical Writing

• Voice AI
• LLM Reasoning
• Agent Systems
• Benchmarking
• Tech Talks