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Machine Learning Engineer - Colgate Palmolive
ML Engineer
Machine Learning Engineer responsible for designing, building, and deploying scalable ML models on AWS, leveraging Python, TensorFlow, and advanced NLP techniques to drive product innovation and data-driven decision making.
About the role
Key Responsibilities
- Design, develop, and production‑grade deploy machine learning models using Python, TensorFlow, and PyTorch on AWS services such as SageMaker and ECS.
- Collaborate with data scientists and product teams to transform business problems into data‑driven solutions, including feature engineering, model selection, and hyper‑parameter tuning.
- Build and maintain end‑to‑end data pipelines, ensuring data quality, scalability, and compliance with privacy regulations.
- Implement continuous integration/continuous deployment (CI/CD) workflows for ML models, monitoring model performance and drift in production.
- Document model architecture, experiments, and results, and present findings to cross‑functional stakeholders.
Requirements
- BS/MS in Computer Science, Data Science, or related field; 3+ years of ML engineering experience.
- Proficiency in Python, SQL, and experience with TensorFlow or PyTorch.
- Hands‑on experience deploying models on AWS (SageMaker, Lambda, ECS, EKS).
- Strong background in data engineering, ETL pipelines, and cloud data services (Redshift, S3, Glue).
- Excellent problem‑solving skills, ability to work independently and in a fast‑paced environment.
Skills
pythonmachine learningawsdeep learningnlptensorflow