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Machine Learning Engineer 174332 - Colgate Palmolive
ML Engineer
Lead end‑to‑end ML development, building scalable models on AWS, integrating data pipelines, and deploying solutions with Docker. Drive product insights and innovation in a fast‑moving analytics environment.
About the role
Key Responsibilities
- Design, develop, and production‑grade machine learning models using Python, TensorFlow, and PyTorch.
- Build and maintain data pipelines and feature stores on AWS (S3, Glue, Redshift, SageMaker).
- Collaborate with data scientists, product managers, and software engineers to translate business problems into ML solutions.
- Deploy models as containerized services with Docker and orchestrate with AWS ECS/EKS.
- Monitor model performance, implement A/B testing, and iterate for continuous improvement.
Requirements
- 5+ years of experience in machine learning engineering or related field.
- Strong proficiency in Python, SQL, and AWS services (SageMaker, Glue, Redshift).
- Hands‑on experience with TensorFlow/PyTorch and Docker containerization.
- Solid understanding of data engineering concepts and large‑scale data processing.
- Excellent communication skills and ability to work cross‑functionally in a dynamic environment.
Skills
pythonmachine learningawssqltensorflowdocker