Machine Learning Engineer

Colgate-Palmolive is hiring a Machine Learning Engineer to drive high-priority machine learning efforts within the Enterprise AI/ML Center of Excellence. The position emphasizes production readiness, reliable orchestration of data and ML workflows, statistical validation, and strong MLOps and DevOps practices to deliver compliant solutions.

Role Summary

In this role, you will help transition ML capabilities from experimentation to production. You will design and maintain the pipelines that support model performance over time, apply rigorous statistical methods to validate outcomes, and use modern engineering workflows to manage the ML and software lifecycle in a CI/CD environment.

Responsibilities

• Productionize ML research: Convert experimental models into robust, scalable production services, including the supporting pipeline infrastructure.
• Orchestrate data and ML pipelines: Build and maintain complex pipelines using Airflow and dbt to support data integrity and model reliability.
• Apply statistical rigor: Use advanced statistical modeling and hypothesis testing to validate models so results remain testable and trustworthy.
• Implement DevOps and MLOps: Apply modern developer tooling within ML and software lifecycle processes, including work aligned to CI/CD practices.

Required Qualifications

• Education: Bachelor’s Degree (or higher) in a high-rigor field such as Statistics, Physics, Chemistry, Mathematics, Data Science, or Computer Science with a heavy emphasis on Statistical Learning.
• Experience: For a Bachelor’s degree, 6+ years of technical experience; for a Masters or PhD, 3+ years.

Technical Skills

• Airflow
• dbt
• Python
• SQL
• Scikit-learn
• Docker
• Kubernetes
• CI/CD
• Git

Preferred Qualifications

• Proven expertise in Data Science and/or Machine Learning Engineering.
• Advanced production-grade proficiency in Python and SQL.
• Hands-on experience with Airflow (orchestration) and dbt (transformation).
• Familiarity with modern IDEs and agentic coding systems such as Cursor, Windsurf, Claude Code, and Antigravity to increase output velocity.
• Expert knowledge of a modern Python and Scikit-learn ML stack and major ML libraries.
• Deep understanding of the data lifecycle (ETL/ELT), data architecture, and best practices for templatized data transformation.
• Familiarity with Docker/Kubernetes, CI/CD, Git, and “Software Engineering for ML” best practices.
• LLM literacy, including concepts underpinning LLMs and strategies to integrate GenAI into the MLE project lifecycle.

Compensation and Location

• Location: New York, NY (onsite)
• Salary: USD 130,000 - 170,000 per yearly

Benefits

• Comprehensive benefits package including medical, dental, vision, and basic life insurance
• Paid parental leave
• Disability coverage
• Participation in the 401(k) retirement plan with company matching contributions, subject to eligibility requirements
• Minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours)
• 13 paid holidays (vacation days are prorated based on the employee’s hire date within the calendar year)
• Paid sick leave adjusted based on role and location in accordance with local laws