Sr. Machine Learning Engineer

About the role

We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X, AppFolio's AI-native platform. 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. You will collaborate with Product, Voice channel, and ML Platform teams to translate cutting-edge agent and voice research into reliable, low-latency, multi-channel experiences that scale across our entire customer base.

Responsibilities

• 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.

Skills

• 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
  • 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.

Pay

The compensation that we reasonably expect to pay for this role is $167,200 - $209,000 base pay. The actual compensation will be determined by a variety of factors, including but not limited to the candidate’s skills, education, experience, and internal equity.

Benefits

Regular full-time employees are eligible for benefits, including a comprehensive Total Rewards package. Additional benefits or discretionary bonuses may be available based on role and employment type.

• Grow: Opportunities for growth and compelling total rewards through high-performance culture and challenging, meaningful work.
• Learn: Investment in your development from the start, including coaching, mentorship, and tools to develop your skills.
• Impact: Innovate with purpose and contribute to a culture of impact, creating effortless experiences for communities.
• Connect: Hybrid work environment fostering flexibility, collaboration, and connection.