Staff Machine Learning Engineer

The Staff Machine Learning Engineer (player-coach) will design, build, test, and deploy production agentic and LLM-powered AI products, along with the platform capabilities that support them. This role combines software-engineering rigor for stateful and transactional systems with practical classical ML and experimentation, operating primarily on Google Cloud.

Responsibilities

• Design, build, test, and deploy production agentic and LLM-powered products end-to-end on Google Cloud, including the shared platform, tooling, and harnesses beneath them.
• Apply strong software-engineering rigor to services that include stateful and transactional (OLTP) systems, with attention to data modeling, concurrency, idempotency, reliability, observability, and testing.
• Use classical machine learning, statistics, and experimentation when appropriate, including predictive modeling, statistical inference, hypothesis testing, and causal or incrementality measurement.
• Build scalable tools for automation across recommendation and personalization, conversational and customer experiences, and measurement and incrementality.
• Write design documents, uphold standards for clean code and documentation, and review designs and deliverables produced by others.
• Mentor and grow engineers and scientists, including support for early-career and student mentorship efforts.
• Partner with engineering, product, and domain-expert teams on cross-functional automation, measurement, and modeling initiatives.
• Participate in Estee Lauder’s diversity and inclusion agenda.

Requirements

• BS/BA in a quantitative or technical field (examples include Computer Science, Statistics, Mathematics, Physics, Engineering, Operations Research, Economics) or equivalent practical experience; a graduate degree is a plus.
• 5+ years of experience (3+ with a graduate degree) across Software Engineering, Machine Learning, and/or Data Science.
• Strong general software engineering in Python, including clean API and service design, proficiency with data structures and algorithms, and disciplined testing. Experience building and operating production-grade services, including stateful or transactional systems and databases (SQL and/or NoSQL).
• Experience deploying and operating LLM-powered or agentic systems in production (such as retrieval-augmented generation, agents and tool use, structured outputs, evaluation, and safety) or a strong production-ML background with a clear interest in this work.
• Experience deploying and operating systems on a major cloud platform, with scalable data-processing practices (Google Cloud is a plus).
• Uses agentic or AI-assisted development tools, or is eager to adopt them with strong judgment about where they help and how to maintain quality.
• A track record of mentorship, continuous learning mindset, bias for simplicity, and a collaborative shared-ownership approach.

Technologies

• Python
• Google Cloud
• SQL
• NoSQL
• Retrieval-augmented generation
• LLM-powered systems
• Agentic systems
• Vertex AI
• Cloud Run
• BigQuery
• Firestore
• Pub/Sub
• FastAPI
• Container-based CI/CD
• Model Context Protocol (MCP)

Benefits

• Health insurance coverage (medical, dental, and vision insurance)
• Wellness and family support programs
• Life and disability insurance
• Retirement savings plans
• Paid leave programs
• Education-related programs
• Paid holidays and vacation time
• Bonus program (highly competitive) with the possibility for overachievement
• Participation in the share incentive plan

Preferred / Strong Plus

• Depth in classical ML, data science, and statistics, including statistical modeling, hypothesis testing and experimentation, causal inference and incrementality, and predictive modeling.
• Hands-on experience in NLP, agent frameworks, or advanced statistical methods.
• Familiarity with the stack: Google Cloud (Vertex AI, Cloud Run, BigQuery, Firestore, Pub/Sub), async Python (FastAPI), container-based CI/CD, and Model Context Protocol (MCP).
• Experience designing a technical roadmap and leading execution in a business environment.

Pay Range

• The anticipated base salary range is $119,300.00 to $196,600.00.
• Exact salary depends on factors such as experience, skills, education, and budget.
• Salary range may vary based on geographic location.
• In addition to base salary, the position is eligible for participation in a highly competitive bonus program and participation in the share incentive plan.

Location

New York, NY (onsite)