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Sr AI ML Engineer (Guadalajara, JAL, MX)
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Job Description
Req ID: 380037 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now.
We are currently seeking a Sr AI ML Engineer (Remote) to join our team in Guadalajara, Jalisco (MX-JAL), Mexico (MX).
Who we’re looking for Toyota’s OneTech Data department is seeking a motivated Machine Learning Engineer to contribute to building scalable machine learning solutions that enhance customer intelligence and support business decision-making.
Reporting to the Customer Data Science Manager at the Office of Data Science and Automation, you will collaborate with cross-functional teams to develop and deploy machine learning models that optimize marketing investments and improve customer engagement.
What you’ll be doing Develop and implement machine learning models such as recommendation engines, customer segmentation, and predictive analytics to support customer-centric business initiatives. Collaborate with data scientists and engineers to translate business requirements into technical solutions.
Write clean, maintainable, and production-quality code primarily in Python, PySpark, and SQL. Assist in building and maintaining data pipelines and workflows using Spark, Airflow, or similar tools. Participate in model validation, testing, and deployment processes.
Communicate findings and model insights effectively to both technical and non-technical stakeholders. Work in an agile environment alongside product managers, data scientists, and engineers to deliver data-driven products.
What you bring Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or related quantitative field. 2-4 years of professional experience in machine learning or data engineering roles.
Solid understanding of machine learning algorithms and experience applying them to real-world problems. Proficiency in Python and SQL; experience with PySpar
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