Machine Learning Engineer Jobs

About The Position

Requirements

• 7+ years of experience developing and scaling web-based applications, preferably in a SaaS environment.
• Experience building and supporting production ML systems at scale.
• Experience building and scaling production ML infrastructure with meaningful business impact.
• Experience leading architectural discussions, defining system design, and guiding technical decision-making.
• Has trained or fine-tuned language models end-to-end and is comfortable with deep learning, evaluation, and inference.
• Hands-on experience with LangChain or LangGraph and modern RAG patterns over structured and unstructured data.
• Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems, especially in agentic contexts.
• Ability to think in terms of platforms and long-term leverage and understand how ML infrastructure decisions compound over time.
• Ability to work effectively amid ambiguity and turn unclear infrastructure problems into clear direction.
• Ownership mindset, urgency, and focus on outcomes.
• Collaborative, humble, low-ego approach across ML, product, and engineering.
• Reliability mindset that includes SLOs, on-call, observability, and postmortems.
• Values work-life balance as a foundation for sustained high performance.

Nice To Haves

• Bachelor’s, Master’s, or Ph.D. in Computer Science or a related technical discipline.
• Experience building ML systems for conversational AI, leasing, or CRM-adjacent workflows.
• GPU performance tuning experience with vLLM, TensorRT, Triton, or similar tools.
• Experience with ontology-driven systems or knowledge graphs supporting AI applications.
• Familiarity with real estate, property management, or leasing workflows.
• Contributions to open-source ML infrastructure or LLM tooling.

Responsibilities

• Define and drive the machine learning roadmap across Leasing products, identify high-leverage opportunities, make model and architecture decisions, and align with Product and Engineering leadership on a technical vision focused on customer outcomes.
• Lead ML development and architecture for AppFolio's autonomous leasing agent, including model quality, evaluation frameworks, and continuous improvement.
• Partner with Voice & Agents and Research ML to evaluate fine-tuning approaches, retrieval strategies, and agentic patterns, deciding which capabilities are ready for production.
• Build evaluation and experimentation infrastructure, define quality measures for leasing-specific tasks, and own metrics tied to customer outcomes.
• Establish ML integration patterns, standards, and practices for Leasing Engineering, including prompt engineering, RAG, fine-tuning, and model selection.
• Ensure production ML systems meet SaaS reliability expectations through SLOs, observability, cost discipline, and an effective on-call posture.
• Lead architectural discussions, define system designs, and guide technical decision-making.
• Understand leasing workflows and use that domain knowledge to guide technical decisions.

Benefits

• Regular full-time employees are eligible for benefits; details are referenced on the company site.
• Total Rewards package, with potential eligibility for discretionary bonuses based on role and employment type.
• Opportunities for growth and compelling total rewards.
• Coaching and mentorship, with time and tools to develop skills.
• Hybrid work environment described as flexible, personal, and connected.