Designs, builds, and scales AI platform infrastructure including agent orchestration, RAG, eval tooling, and model serving for internal teams. Requires 12+ years AI/ML experience, expertise in LLMs/NLP, Python proficiency, and ML frameworks like PyTorch.
245k – 321k/yr
Hybrid12+ YOEML Engineering
About the role
Responsibilities
Design and build scalable platform services — agent orchestration, RAG pipelines, eval frameworks, model serving — that internal teams use to ship AI-powered products.
Lead technical strategy and architecture for the AI platform, including model lifecycle, observability, safety guardrails, and evaluation infrastructure.
Collaborate cross-functionally with app teams, PMs, and Designers to understand their AI needs and deliver platform capabilities that unblock them.
Build, harden, and operate shared infrastructure that powers intelligent agents across Gusto (e.g., retrieval, routing, prompt management, content selection).
Stay current with AI/ML research; rapidly prototype and productionize new techniques that strengthen the platform.
Establish robust practices for validation, deployment, monitoring, and ongoing performance management of platform services and the agents built on them.
Communicate technical strategy, tradeoffs, and impact clearly to executives and non-technical partners.
Mentor engineers across teams, raising the bar on AI/ML best practices and fostering a culture of pragmatic innovation.
Requirements
12+ years building and deploying end-to-end AI/ML systems, with experience designing platform-level infrastructure that other engineering teams build on.
Deep expertise in one or more areas: LLMs, NLP, retrieval/RAG, agent orchestration, deep learning, or reinforcement learning.
Hands-on experience building LLM-based applications and agentic workflows — including prompt engineering, retrieval design, evaluation, and production deployment.
Proficiency with modern ML frameworks (PyTorch, TensorFlow, Hugging Face) and cloud platforms (GCP, AWS, or Azure).
Strong Python skills and sound software engineering fundamentals — testing, code review, CI/CD, reliability, and API design.
Proven track record shipping impactful AI/ML projects to production, ideally in a platform or infrastructure context.
Demonstrated ability to lead cross-functionally, influence technical direction, and communicate clearly with both engineers and non-technical stakeholders.
Nice-to-Haves
Ph.D. or Master's in CS, ML, Statistics, Mathematics, or related field.
Compensation
Targeted at $245,000-272,000 in Denver & most remote locations.
Senior technical leader building, productionizing and operating large-scale ML models and Agentic AI systems to fight fraud, ensure safety and build trust across Airbnb's platform. Requires 12+ years applied ML experience and deep expertise in LLMs/GenAI.
244k – 305k/yr
Remote12+ YOEML Engineering
Senior Staff Machine Learning Engineer, Communication & Connectivity
AirbnbUnited States
Lead ML architecture and implementation for Airbnb's Messaging & Notifications, building recommendation engines, ranking systems, and LLM-powered experiences while mentoring engineers.
Develops and productionizes AI/ML models and pipelines at scale for Airbnb's agentic growth platform, powering personalized content generation, decisioning, and proactive marketing agents. Requires 12+ years experience, strong programming, and expertise in ML best practices and tools like PyTorch and Kubernetes.
244k – 305k/yr
Remote12+ YOEML Engineering
Senior Staff Machine Learning Engineer, Community Support Engineering
AirbnbUnited States
Senior ML engineer leads development of GenAI models and pipelines for Airbnb's customer support, productionizing at scale. Requires PhD, 10+ years ML experience including 2+ in GenAI, and expertise in NLP, deep learning, and agile AI practices.
244k – 305k/yr
Remote10+ YOEML Engineering
Senior Staff Machine Learning Engineer, Post Training
AirbnbUnited States
Senior Staff ML Engineer fine-tunes and optimizes state-of-the-art LLMs for Airbnb's customer support AI products, including AI assistants and autonomous agents. Partners cross-functionally to productionize models at scale. Requires PhD and 10+ years experience with PyTorch.