Sr. Machine Learning Engineer

Who We Are Looking For

We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio's production voice and chat agent pipelines, working at the intersection of LLM agent frameworks, real-time voice technology, and streaming infrastructure.

Your Impact

• Ship Voice & Text Agents: Architect and ship voice and text agent pipelines that handle real-time, multi-turn customer interactions.
• Reasoning vs. Latency: Make principled trade-offs between reasoning depth and latency across frontier LLMs, smaller models, and routing strategies.
• Lead a Pod: Lead a small pod of ML and platform engineers; raise the bar on agent evaluation, observability, and incident response.
• Define Quality: Partner with Product and Voice channel teams to define KPIs, eval harnesses, and acceptance criteria for agent quality.
• Optimize for Voice: Drive selective Small Language Model (SLM) fine-tuning and inference optimization for voice latency and cost.

Qualifications

• You have shipped production AI agents serving real users in voice and/or text channels.
• You think in pipelines and systems, not just models.
• You move fast, deliver impact, and maintain sound engineering judgment.
• You are humble, collaborative, and low-ego, and you elevate those around you.
• You value work-life balance as a foundation for sustained high performance.

Must Have

• Agent frameworks: Deep, shipped experience with LangChain, LangGraph, LangSmith, and LangChain Deep Agents (or equivalent agent frameworks).
• Voice stack: Hands-on with Voice-to-Voice models and traditional TTS / STT pipelines; understands the trade-offs between end-to-end voice models and modular STT → LLM → TTS architectures.
• LLM fluency: Strong grasp of LLM reasoning behavior, tool use, structured output, and reasoning-vs-latency trade-offs across providers.
• Telephony & cloud: Production experience with Twilio (or comparable telephony) and AWS.
• Engineering: Expert Python, async programming, and WebSockets for real-time, bidirectional streaming.
• ML fundamentals: Solid foundation in deep learning, model evaluation, and inference optimization; able to deploy with Docker on AWS.
• Leadership: Demonstrated ability to lead a small team, mentor engineers, and partner credibly with Product and Design.

Nice to Have

• Fine-tuning Small Language Models for domain-specific voice applications.
• Familiarity with RAG over structured business data and tool-using agents over API surfaces.
• Prior experience in regulated or customer-facing industries with strict reliability requirements.
• Publicly verifiable work on GitHub, in open-source agent frameworks, or in community competitions.