Principal Machine Learning Scientist – Agentic Experiences

Jobtailor; California (MO); On-site; USD 150,000 - 190,000; Full time

Job summary

Jobtailor is seeking an experienced Lead ML Engineer to architect agentic AI systems and drive production-grade implementations. You will integrate LLMs with external tools, design evaluation frameworks, and collaborate across product, engineering, and research teams.

The role emphasizes mentoring senior engineers, advancing agentic architectures (ReAct, reflection loops), and ensuring safe, scalable deployments in a fast-moving environment.

Qualifications

• BS in Computer Science, Machine Learning, Statistics, Engineering, or related field, or equivalent experience
• 10+ years of related industry experience
• Experience designing and deploying agentic or multi-step AI systems in production or research
• 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 ML Engineering teams
• Advanced degree preferred
• Experience in travel or e-commerce preferred
• Publications or patents preferred
• Open-source contributions preferred

Responsibilities

• Design, develop, and evaluate multi-step AI systems with planning and tool use
• Research and implement agentic architecture techniques (ReAct, reflection loops)
• Develop agent orchestration frameworks for task decomposition and recovery
• Integrate LLMs with external tools, APIs, databases, and code execution
• Define evaluation frameworks measuring reliability, latency, cost, and safety
• Collaborate with product, engineering, and research to translate requirements
• Identify and mitigate risks like prompt injection and hallucinations
• Synthesize research to inform technical direction
• Mentor senior ML engineers on agentic design and experimentation

Skills

Agentic AI System Design

Python Proficiency

LLM API Integration

ML System Evaluation

Mentoring

Production Monitoring

Task Decomposition

Tool-Augmented Reasoning

Multi-Agent Collaboration

Education

Bachelor's degree in CS/ML/Engineering

Advanced degree preferred

Tools

PyTorch

TensorFlow

JAX

LangChain

LlamaIndex

APIs

Databases

Code Execution Environments

Job description

• 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