Senior Machine Learning Scientist

Key Responsibilities

• Design, build, and evaluate multi-step agentic AI systems, including autonomous agents capable of:
• Planning and goal decomposition
• Tool selection and execution
• Memory and state management
• Multi-agent collaboration and coordination
• Research and implement state-of-the-art agentic architectures, including:
• ReAct and tool‑calling agents
• Reflection and self‑improvement loops
• Chain‑of‑thought and structured reasoning
• Tool‑augmented and hybrid agent frameworks
• Develop and evolve agent orchestration approaches, defining how agents:
• Delegate to sub‑agents
• Handle uncertainty, failure, and recovery
• Integrate LLMs with external tools, APIs, databases, and code execution environments to enable real‑world task completion.
• Define and own scientific evaluation frameworks for agentic systems, measuring:
• Task success and reliability
• Generalization and robustness
• Latency, cost, and efficiency
• Safety and unintended behaviors
• Collaborate closely with Product, Engineering, and Research partners to translate business and user needs into well‑scoped scientific problems and agentic system designs.
• Identify and mitigate agent‑specific risks, including:
• Prompt injection and adversarial inputs
• Hallucination in long‑horizon reasoning
• Unsafe or unintended tool actions
• Stay current with the rapidly evolving agentic AI research landscape, synthesizing academic literature and industry innovation to guide technical strategy.
• Mentor junior ML scientists and engineers, providing guidance on:
• Scientific rigor and evaluation methodology

Minimum Qualifications

• 10+ years of related industry or research experience in machine learning or applied AI.
• Demonstrated experience designing and evaluating agentic or multi‑step AI systems, such as:
• ReAct‑style agents
• Tool‑using or planner‑based agents
• Multi‑agent systems or pipelines
• Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX.
• Hands‑on experience with LLM APIs and agent frameworks, including:
• Similar orchestration or agent libraries
• Experience integrating LLMs with external tools, APIs, and structured data sources for real‑world tasks.
• Solid understanding of prompting and reasoning techniques, including:
• Chain‑of‑thought
• Few‑shot and zero‑shot prompting
• Structured output and constrained decoding
• Experience designing and running evaluation frameworks for ML systems, including offline benchmarks 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 travel, e‑commerce, marketplace, or advertising platforms.
• Publications in top‑tier ML conferences or journals.
• Patented inventions, pending or issued.
• Contributions to open‑source ML / LLM / agentic AI projects.
• Experience partnering with ML Engineering teams to transition research prototypes into production systems.

Work Authorization

Must be authorized to work in the United States and hold a valid passport.

Benefits

• Operating with the brightest minds in the hotel software industry
• Receiving global exposure
• Benefiting from continuous learning programs
• Performance‑based career growth
• Competitive compensation that includes fixed compensation, variable compensation based on achieving set sales goals, company‑paid employee benefits, vacation, sick and personal leave, and company‑matched 401(k).

IBS is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, protected veteran status or any other characteristic protected by law. IBS as an equal opportunity employer bases its hiring decisions on the business need and the best qualified candidates available, and does not discriminate in its employment decisions on the basis of any protected category. Candidates who are offered employment may be subject to a criminal record and other background checks as permitted or required by company policy or applicable law.