Machine Learning Engineer

No Relocation Assistance Offered
Job Number #174332 - New York, New York, United States

Who We Are

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!

Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.
 

*This role can sit in our Park Ave (NYC) or Piscataway, NJ office*

 

Role Summary

We are seeking a Machine Learning Engineer who brings the analytical rigor of a data scientist and the engineering discipline of a software architect. In support of Colgate-Palmolive’s purpose to Make More Smiles and our commitment to a healthier future for our people, pets, and planet, this role builds the advanced machine learning capabilities that power smarter decisions, accelerate innovation, and create measurable impact across our global enterprise.

As part of the Enterprise AI/ML Center of Excellence, you will lead the architectural design and end-to-end execution of high-priority ML initiatives. This involves integrating statistical modeling, optimization, and autonomous workflows into Colgate-Palmolive's business processes to accelerate innovation, enhance decision intelligence, and embed AI. Beyond hands-on technical work, you ensure solutions are architecturally sound, production-ready, and compliant with enterprise governance standards, translating strategy into robust execution aligned with stakeholder needs and long-term value creation.

 

Responsibilities:

• Productionize ML Research: Transition experimental models into robust, scalable production services. You don't just build the model; you build the pipeline that sustains it.

• Pipeline Orchestration: Design and maintain complex data and ML pipelines using Airflow and dbt to ensure data integrity and model reliability.

• Statistical Rigor: Apply advanced statistical modeling and hypothesis testing to validate models, ensuring outcomes are testable and honest.

• DevOps & MLOps: Utilize modern developer tools to work within and CI/CD frameworks for ML and software lifecycle management

 

Required Qualifications: 

• Bachelor’s Degree (or higher) in a high-rigor field: Statistics, Physics, Chemistry, Mathematics, Data Science, or Computer Science with a heavy emphasis on Statistical Learning.

• Experience: Bachelors degree: 6+ of  years of technical experience; Masters or PhD (3+ years) 

 

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 (e.g., Cursor, Windsurf, Claude Code, Antigravity) to maximize output velocity.

• Modern Stack: Expert knowledge of Python, Scikit-learn, major ML Libraries

• Data Engineering: Deep understanding of data lifecycle (ETL/ELT), data architecture, best practices for templatized data transformation

• Engineering Excellence: Familiar with Docker/Kubernetes, CI/CD, Git, and "Software Engineering for ML" best practices.

• LLM Literacy: Familiar with concepts underpinning LLMs, and strategies to integrate GenAI into MLE project lifecycle

Compensation and Benefits
Salary Range $130,000.00 - $170,000.00 USD

Pay is determined based on experience, qualifications, and location. Salaried employees may also be eligible for discretionary bonuses, profit-sharing, and long-term incentives for Executive-level roles.

Benefits: Salaried employees enjoy a comprehensive benefits package, including medical, dental, vision, basic life insurance, paid parental leave, disability coverage, and participation in the 401(k) retirement plan with company matching contribut