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Senior Machine Learning Scientist - Agentic Experience
- Seattle, Washington, United States
- Seattle, Washington, United States
Über
Design, build, and evaluate multi‑step agentic AI systems, including autonomous agents capable of planning, tool use, memory management, and multi‑agent collaboration. Research and implement state‑of‑the‑art techniques in agentic architectures, such as ReAct, reflection loops, chain‑of‑thought prompting, and tool‑augmented reasoning. Develop and maintain agent orchestration frameworks, defining how agents decompose tasks, delegate to sub‑agents, and handle failure and recovery. Integrate large language models (LLMs) with external tools, APIs, databases, and code‑execution environments to enable real‑world task completion. Define and own evaluation frameworks for agentic systems, measuring task success, reliability, latency, cost and safety across diverse benchmarks and production scenarios. Collaborate closely with product, engineering, and research teams to translate business requirements into agentic system designs and deliver production‑grade solutions. Identify and mitigate risks specific to agentic systems, including prompt injection, unintended actions, hallucination in long‑horizon tasks and unsafe tool use. Stay current with the rapidly evolving agentic AI landscape, synthesizing academic research and industry developments to inform the team’s technical direction. Mentor junior ML engineers and scientists, providing technical guidance on agentic design patterns, LLM best practices, and experimentation methodology.
Minimum Qualifications
8+ years of related industry experience. Demonstrated experience designing and deploying agentic or multi‑step AI systems (e.g. ReAct, tool‑calling agents, multi‑agent pipelines) in production or research settings. Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX); experience with LLM APIs and orchestration libraries such as LangChain, LlamaIndex or similar. Experience integrating LLMs with external tools, APIs and structured data sources for real‑world task completion. Solid understanding of prompt engineering techniques including chain‑of‑thought, few‑shot prompting and structured output generation. Experience defining and running evaluation frameworks for ML systems, including offline benchmarking and production monitoring.
Preferred Qualifications
PhD, MS or BS in Computer Science, Machine Learning, Statistics, Engineering or a related field; or equivalent professional experience. Experience in the travel or e‑commerce industry. Publications in top‑tier ML conferences or journals. Patented inventions, pending and issued. Contributions to open‑source ML projects. Experience taking models from prototype to production in collaboration with Machine Learning Engineering teams.
Salary and Compensation San Jose: $187,000–$261,500 (potential up to $299,000). Seattle: $173,000–$242,500 (potential up to $277,000). Austin: $173,000–$242,500 (potential up to $277,000). Starting pay varies by location, budget and experience. Benefits Medical, dental and vision coverage; paid time off; Employee Assistance Program; wellness and travel reimbursement; travel discounts; International Airlines Travel Agent (IATAN) membership. 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. Equal Employment Opportunity Statement 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, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status. This employer participates in E‑Verify. The employer will provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee’s I‑9 to confirm work authorization. #J-18808-Ljbffr
Sprachkenntnisse
- English
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