Machine Learning Engineer

Colgate Palmolive
New York, NY, United States
2 days ago
Apply on www.juju.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$130,000.0 - $170,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Airflow Application Lifecycle Management Continuous Integration Data Architecture Information Engineering Data Integrity Extract Transform Load (ETL) Data Transformation Cursor (Graphical User Interface Elements) DevOps Programming Tools
+14 more
Statistical Hypothesis Testing Python (Programming Language) Machine Learning Software Engineering SQL Databases Large Language Models Deep Learning Git Scikit Learn Kubernetes Information Technology Machine Learning Operations Data Pipelines Docker

Job description

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, Our journey begins with our people-developing strong talent with diverse backgrounds and perspectives to best serve our consumers around the world and fostering an inclusive environment where everyone feels a true sense of belonging. We are dedicated to ensuring that each individual can be their authentic self, is treated with respect, and is empowered by leadership to contribute meaningfully to our business.

Requirements

  • 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

Benefits & conditions

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 contributions subject to eligibility requirements. Additional benefits include a minimum of 15 vacation/PTO days (hourly employees receive a minimum of 120 hours) and 13 paid holidays (vacation days are prorated based on the employee’s hire date within the calendar year). Paid sick leave is adjusted based on role and location in accordance with local laws. Detailed information regarding paid sick leave entitlements will be provided to employees upon hiring and may be subject to adjustments based on changes in legislation or company policies.

About the company

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

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.juju.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:07 min

Inspecting default bridge architectures and custom Docker networks

Oliver Seitz Oliver Seitz · World Congress 2025

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · World Congress 2026 Europe

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

Videos

See all

Related articles

See all