Machine Learning Engineer

Colgate-Palmolive is building production-ready machine learning capabilities through its Enterprise AI/ML Center of Excellence, and is hiring a Machine Learning Engineer based in New York, NY (onsite). This role focuses on turning high-priority ML work into compliant, scalable solutions by combining production engineering, pipeline orchestration, and statistical validation.

With a salary range of USD 130,000 - 170,000 per year, you will help deliver ML services that are not only accurate, but also maintainable in real production environments.

Responsibilities

• Productionize ML research: transition experimental models into robust, scalable production services, including the pipeline and operational support that sustain them.
• Orchestrate data and ML pipelines: design and maintain complex pipeline workflows using Airflow and dbt to support data integrity and model reliability.
• Apply statistical rigor: perform advanced statistical modeling and hypothesis testing to validate models and ensure outcomes remain testable and trustworthy.
• Build with DevOps and MLOps practices: use modern developer tools and work within CI/CD frameworks to manage the ML and software lifecycle.

Requirements

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

Technologies

You will work with Airflow, dbt, Python, SQL, Scikit-learn, Docker, Kubernetes, CI/CD, and Git.

Benefits

• Comprehensive benefits package including medical, dental, vision, and basic life insurance.
• Paid parental leave.
• Disability coverage.
• 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.

Preferred Qualifications

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