Manager, Machine Learning Engineering

Job Title Manager, Machine Learning Engineering Job Details Location: New York, New York, United States Travel Required: up to 10% of time Hybrid No Relocation Assistance Offered Overview The Manager, Machine Learning Engineering is a technical leader who bridges the gap between enterprise AI strategy and production grade execution. In alignment with Colgate-Palmolive's purpose to Make More Smiles and our commitment to a healthier future for our people, pets, and planet, this role ensures that advanced machine learning capabilities are translated into scalable, responsible solutions that deliver measurable business impact across our global operations. 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 Architectural Design: Lead the design of scalable, modular ML architectures. Define how models, data pipelines (Airflow/dbt), and inference services integrate with enterprise applications and cloud infrastructure (GCP). Project Management: Own the full ML lifecycle for key enterprise workstreams. Manage resource allocation, sprint planning, and delivery timelines to ensure “moonshot” projects move from lab to production. Stakeholder Management: Act as the primary technical point of contact for business partners in Marketing, Supply Chain, and Finance. Translate complex business problems into technical requirements and communicate project impact through data-driven narratives. Production Excellence: Oversee the transition of experimental research into robust production services. Ensure all systems meet enterprise standards for MLOps, security, and reliability. Technical Governance: Ensure that architectural patterns and coding standards are followed across the team, conducting design reviews and code audits to maintain “Software Engineering for ML” best practices. Required Qualifications Bachelor’s Degree (or higher) in a high-rigor field: Statistics, Data Science, Computer Science, Physics, or Mathematics Industry Experience: 6+ years of experience in Data Science or ML Engineering, with at least 2 years in a project leadership or supervisory capacity. Architecture & Systems: Proven track record of designing and deploying deeply integrated ML use cases that span multiple business workflows. Stack Expertise: Expert-level proficiency in Python (production-grade), SQL, and GCP. Hands‑on experience architecting pipelines with Airflow and dbt. Velocity Tools: Advanced proficiency with Agentic Coding systems (e.g., Cursor, Windsurf) to accelerate the project lifecycle. System Design: Deep understanding of MLOps, containerization (Docker/Kubernetes), and CI/CD frameworks. Statistical Depth: Mastery of Bayesian methods, causal inference, and predictive modeling techniques to ensure model validation. Modern AI Integration: Ability to design strategies that integrate LLMs and Generative AI into traditional ML workflows (e.g., using LLMs to automate processes). Data Engineering: Expertise in data lifecycle management (ETL/ELT) and templatized data transformation. Preferred Qualifications Project Leadership: Mastery of Agile/Scrum methodologies for ML development. Strategic Narrative: Exceptional ability to back technical data with a compelling business story for C-suite stakeholders. Problem-solving: Ability to decompose ambiguous business challenges into modular, actionable technical architectures. Collaborative Influence: Adept at navigating a global, matrixed environment to drive alignment across IT, Legal, and Commercial teams. Ph.D. in a quantitative field with an understanding of Statistical Learning or Optimization. Compensation and Benefits Salary Range: $120,000.00 – $191,000.00 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: 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. 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. Our Commitment to Inclusion 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. Equal Opportunity Employer Colgate is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, ethnicity, age, disability, marital status, veteran status (United States positions), or any other characteristic protected by law. Reasonable accommodation during the application process is available for persons with disabilities. Job Posting Information Posting Start Date: 5/27/26 #J-18808-Ljbffr