Staff Machine Learning Engineer

AppFolio Inc is building ML capabilities that power Realm-X, and this role is focused on advancing the platform across training, fine-tuning, inference, RAG, and evaluation. You will help operate an always-on, observable, economical machine learning infrastructure on AWS, while partnering with teams to productionize research with strong cost discipline and AI safety and authorization.

What you’ll work on

• Design and operate AppFolio’s ML infrastructure on AWS including ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls.
• Optimize cost across AI applications using provider routing, caching, batch vs. real-time approaches, model size selection, and inference economics.
• Maintain reliable multi-provider LLM access across Google, OpenAI, and Anthropic, with sensible fallbacks and shared abstractions.
• Build the training and fine-tuning stack for Small Language Models, including data pipelines, GPU orchestration, and evaluation.
• Partner with Voice & Agents and Research ML engineers to harden prototypes into production systems with SLOs, on-call rotations, and observability.
• Operate AppFolio’s AI safety and authorization layer with guardrails on AWS, scoped tool permissions, and human-in-the-loop gates for autonomous agent actions.

Requirements

• 7+ years developing and scaling web-based applications, preferably in a SaaS environment.
• Systems thinker who focuses on platforms and long-term leverage.
• Production builder with experience scaling ML infrastructure with business impact.
• Comfort operating in high ambiguity and turning unclear infrastructure issues into clear direction.
• Owner-operator mindset with urgency, outcome focus, and high engineering judgment.
• Collaboration with low-ego communication and a tendency to elevate others.
• Commitment to work-life balance as a foundation for sustained performance.
• Reliability mindset treating ML infrastructure like production software, including SLOs, on-call, observability, and postmortems.
• Hands-on experience operating production ML infrastructure on AWS including ECS, SageMaker, GPUs, autoscaling, and cost controls.
• Production experience with model serving for both LLMs and custom models, including understanding quantization, batching, and routing.
• Direct production integration experience with Google (Vertex / Gemini), OpenAI, and Anthropic APIs.
• Ability to train or fine-tune language models end-to-end, including deep learning, evaluation, and inference.
• Strong Python, Docker, dependency management, and CI/CD practices for AI workloads.
• Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data.
• Demonstrated ability to reduce unit cost of AI workloads without regressing quality or latency.
• Hands-on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems.

Technologies

• AWS, ECS, SageMaker, GPU fleets
• Python, Docker, CI/CD
• Google (Vertex / Gemini), OpenAI, Anthropic
• LangChain, LangGraph
• RAG, Small Language Models

Nice to have

• Bachelor’s, Master’s, or Ph.D. in Computer Science or a related technical discipline.
• Experience training Small Language Models for production use.
• GPU performance tuning (vLLM, TensorRT, Triton, or similar).
• Prior Staff-level role at a company with a significant AI infra footprint.
• Experience with ontology-driven systems or knowledge graphs supporting AI applications.
• Contributions to open-source ML infrastructure or LLM tooling.

Location

Denver, CO (hybrid). Find out more about locations by visiting the company site. All late-stage candidates complete an in-person meeting with an AppFolian as part of the hiring process.

Compensation & benefits

The expected base pay for this role is $200,000 - $275,000 per year. Actual compensation will be determined based on factors including skills, education, experience, and internal equity.

Compensation is part of a broader Total Rewards package, which may include additional benefits and discretionary bonuses depending on role and employment type. Regular full-time employees are eligible for benefits (see here).

Salary range: USD 200,000 - 275,000 per yearly.