Senior Machine Learning Scientist (LLM & Agents)

We are looking for a Senior Machine Learning Scientist (LLM & Agents) to join the Enterprise Solution Science Team. This team focuses on applying cutting-edge ML technologies to real-world marketing problems by combining them with omnichannel customer data. In this role, you will be responsible for end-to-end development, from problem definition to driving model deployment into production.

Responsibilities

Contribute to the design, development, and productionization of one or more enterprise AI agents (Marketing Agent, Strategy Agent, Sales and Service Agent); Collaborate with product teams to translate product goals and business requirements into well-defined machine learning problems; Work closely with ML engineers to deploy models into production environments with reliability and maintainability; Conduct offline and online evaluation, monitoring, and continuous optimization after deployment; Stay up to date with the latest research and proactively propose innovative applications; Mentor junior scientists

Requirements

Master’s or PhD degree in Computer Science, Machine Learning, Mathematics, Electrical Engineering, or related fields; 3+ years of experience in machine learning or engineering roles; Experience designing, developing, and deploying enterprise LLM / agentic applications, including skills/tools/function calling, AI Protocol (MCP / A2A), workflow orchestration, benchmark evaluation; Experience collaborating across functions and leading industry projects; Impact-driven mindset, strong analytical and problem-solving skills, and passion for learning cutting-edge technologies; Proficient in AI-powered development tools such as: Claude Code, OpenAI Codex / Codex CLI, Cursor, Windsurf, GitHub Copilot

Nice to have

Strong focus on quantitative metrics and systematic evaluation; Industry experience in MarTech and passion for building customer-centric products; Hands-on experience agentic product development, including context engineering, harness engineering, evaluation/testing workflows, human-in-the-loop workflows