Machine Learning Engineer III (Full-Stack Gen AI & Agentic Systems)

Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.

Why Join Us?

To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated and know that when one of us wins, we all win.

We provide a full benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model (with some pretty cool offices), and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey. We’re building a more open world. Join us.

Our Growth Marketing team is redefining how data-driven marketing meets AI-powered, agentic automation. We deploy production-ready multimodal LLMs, GenAI, and agentic NLP architectures that power personalized travel discovery and real-time, cross-platform campaign execution. Our agentic systems scale from personalized recommendations to interactive chatbots like “Trip Matching” on Instagram, transforming inspiring reels and posts into hotel suggestions.

We are seeking a hands-on Machine Learning Engineer III who can build complete end-to-end AI products, including backend pipelines, agent orchestration, inference platforms, and user-facing interfaces with UX/UI design.

In this role, you will:

• Architect, implement, and scale LLM training, fine-tuning, adaptation (LoRA/QLoRA/adapters), and distillation pipelines, including RLHF/DPO for production GenAI systems and chatbots.

• Build and optimize RAG pipelines with vector stores and retrieval memory layers, supporting multimodal data such as vision, audio, text, and music.

• Design and develop agentic workflows using frameworks like LangChain, AutoGen, LangGraph, and OpenAI Agents SDK, including typed tool contracts, schema validation, and retry logic.

• Integrate memory strategies, including vector retrieval, episodic and semantic memory, and context compression, into agent workflows.

• Implement evaluation, safety, and reliability frameworks using LangSmith, DeepEval, and OpenClaw, including automated metrics, hallucination mitigation, and LLM-as-a-Judge evaluation.

• Build and deploy production inference platforms optimized for latency and cost using vLLM, TensorRT-LLM, and DeepSpeed.

• Develop containerized, cloud-ready systems with Docker, AWS, or Azure; implement CI/CD, experiment tracking, and model versioning with MLflow.

• Monitor model drift, agent performance, and tooling reliability, establishing dashboards and alerts.

• Collaborate with ML, Engineering, and Product teams to translate requirements into measurable, user-facing GenAI products.

• Design intuitive user interfaces and experiences for agentic systems, ensuring seamless interaction from frontend to backend.

• Mentor peers on ML system design, distributed training, multi-agent orchestration, prompt engineering, and production deployment.

Experience and Qualifications

Essential Skills:

• 7+ years of software/ML engineering experience building and deploying production ML/GenAI systems.

• Hands-on experience with LLM fine-tuning, adaptation, distillation, RLHF/DPO, and parameter-efficient optimization.

• Experience building RAG and multimodal systems with vector stores and retrieval layers.

• Proficiency in agent development and orchestration using LangChain, AutoGen, LangGraph, OpenAI Agents SDK.

• Strong programming skills in Python and distributed ML tooling (PyTorch).

• Experience with cloud platforms (AWS/Azure) and containerized deployments (Docker).

• Proven track record of delivering end-to-end GenAI products, from backend to user-facing interfaces.

• Familiarity with UX/UI design principles for AI systems and chatbots.

• Deep understanding of context engineering, including retrieval, memory hierarchies, grounding, and evaluation metrics.

Nice To Have:

• Open-source contributions, publications, or conference talks in LLMs, RAG, or agentic systems.

• Experience optimizing large-scale inference using vLLM, TensorRT-LLM, or DeepSpeed.

• Familiarity with observability and evaluation frameworks like LangSmith, DeepEval, and OpenClaw.

• Experience with CI/CD and MLOps tools, such as MLflow.

• Strong communication skills and proven ability to collaborate cross-functionally across product, design, and engineering.

#LI-MF2

Accommodation requests

If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.

We are proud to be named as a Best Place to Work on Glassdoor in 2024 and be recognized for award-winning culture by organizations like Forbes, TIME, Disability:IN, and others.

Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™. © 2024 Expedia, Inc. All rights reserved. Trademarks and logos are the property of their respective owners. CST: 2029030-50

Employment opportunities and job offers at Expedia Group will always come from Expedia Group’s Talent Acquisition and hiring teams. Never provide sensitive, personal information to someone unless you’re confident who the recipient is. Expedia Group does not extend job offers via email or any other messaging tools to individuals with whom we have not made prior contact. Our email domain is @expediagroup.com. The official website to find and apply for job openings at Expedia Group is careers.expediagroup.com/jobs.

Expedia is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.