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Sr. Machine Learning Engineer
AppFolio
USA
Full-time
Senior Level
Hybrid
USD 167200-209000 yearly
Discovered 1 weeks ago
Free
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- 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.
- 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.
- 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.
- Experience 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.
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