Principal Machine Learning Scientist – Agentic Experiences

• Design, build, and evaluate multi-step agentic AI systems with planning, tool use, memory management, and multi-agent collaboration


• Research and implement agentic architecture techniques including ReAct, reflection loops, chain-of-thought prompting, and tool-augmented reasoning


• Develop and maintain 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 and own evaluation frameworks measuring task success, reliability, latency, cost, and safety


• Collaborate with product, engineering, and research teams to translate business requirements into production-grade agentic solutions


• Identify and mitigate agentic-system risks such as prompt injection, unintended actions, hallucinations, and unsafe tool use


• Synthesize academic research and industry developments to inform technical direction


• Mentor senior ML engineers and scientists on agentic design patterns, LLM practices, and experimentation methodology

Requirements

• BS in Computer Science, Machine Learning, Statistics, Engineering, or a related field, or equivalent professional experience


• 10+ years of related industry experience


• Experience designing and deploying agentic or multi-step AI systems in production or research settings


• Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX


• Experience with LLM APIs and orchestration libraries such as LangChain or LlamaIndex


• Experience integrating LLMs with external tools, APIs, and structured data sources


• Understanding of prompt engineering, including chain-of-thought, few-shot prompting, and structured output generation


• Experience defining and running ML-system evaluation frameworks, including offline benchmarking and production monitoring


• Experience taking models from prototype to production with Machine Learning Engineering teams


• Advanced degree in Computer Science, Machine Learning, Statistics, or Engineering is preferred


• Experience in travel or e-commerce is preferred


• Publications in top-tier ML conferences or journals are preferred


• Patented inventions are preferred


• Contributions to open-source ML projects are preferred

Core Competencies

Demonstrates expertise in designing and deploying agentic AI systems, integrating large language models with external tools, and defining evaluation frameworks for performance metrics. Proven ability to mentor teams and translate complex business requirements into effective AI solutions.

Highest-signal resume keywords

• Agentic AI System Design


• Python Proficiency


• LLM API Integration


• ML System Evaluation Frameworks


• Mentoring ML Engineers

ATS Optimization Keywords

Hard Skills

• Machine Learning


• Agentic Architecture Techniques


• Prompt Engineering


• Task Decomposition


• Failure Handling


• Tool-Augmented Reasoning


• Multi-Agent Collaboration


• Production Monitoring


• Benchmarking


• Data Structures

Soft Skills

• Collaboration


• Mentoring


• Research Synthesis


• Problem Solving


• Communication

Industry Keywords

• E-Commerce


• Travel


• Machine Learning Engineering


• Open-Source Contributions


• Publications in ML Conferences

Tools & Technologies

• PyTorch


• TensorFlow


• JAX


• LangChain


• LlamaIndex


• APIs


• Databases


• Code Execution Environments