Machine Learning Scientist II - Agentic Experiences (AI)

Location: United States — San Jose, California; compensation ranges are also listed for Seattle and Austin.

Salary: $122,500–$171,500 total cash range in San Jose, with potential increases up to $196,000. Seattle and Austin ranges are $112,000–$156,500, with potential increases up to $179,000.

Company

hirify.global is a global travel company connecting travelers, partners, and advertisers through consumer brands, B2B travel services, and travel advertising.

What you will do

• Design, build, and evaluate multi-step agentic AI systems with planning, tool use, memory, and multi-agent collaboration.
• Research and implement agentic architectures, including ReAct, reflection loops, chain-of-thought prompting, and tool-augmented reasoning.
• Develop agent orchestration frameworks for task decomposition, delegation, failure handling, and recovery.
• Integrate large language models with external tools, APIs, databases, and code execution environments.
• Define evaluation frameworks measuring task success, reliability, latency, cost, and safety across benchmarks and production scenarios.
• Collaborate with product, engineering, and research teams to deliver production-grade agentic solutions and mitigate risks such as prompt injection, hallucinations, and unsafe tool use.

Requirements

• PhD, MS, or BS in Computer Science, Machine Learning, Statistics, Engineering, or a related field, or equivalent professional experience.
• At least 2 years of related industry experience.
• Experience designing and deploying agentic or multi-step AI systems in production or research settings.
• Proficiency in Python and at least one ML framework: PyTorch, TensorFlow, or JAX.
• Experience with LLM APIs, orchestration libraries such as LangChain or LlamaIndex, and integrations with external tools, APIs, and structured data.
• Experience defining ML evaluation frameworks, including offline benchmarking and production monitoring.

Nice to have

• Experience in travel or e-commerce.
• Publications in top-tier ML conferences or journals.
• Patented inventions or pending patents.
• Contributions to open-source ML projects.
• Experience moving models from prototype to production with Machine Learning Engineering teams.

Culture & Benefits

• Medical, dental, and vision coverage.
• Paid time off and an Employee Assistance Program.
• Wellness and travel reimbursement.
• Travel discounts and IATAN membership.
• Supportive environment focused on traveler-first product development, ownership, excellence, and collaboration.