Sr. ML Ops Engineer
hace 1 semana
Toyota's OneTech Data department is seeking a motivated Mid-Level 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.
- 8+ 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 PySpark or similar big data tools is a plus.
- Familiarity with machine learning frameworks such as TensorFlow or PyTorch.
- Experience with cloud platforms and ML tools like AWS Sagemaker or Databricks preferred but not required.
- Ability to work collaboratively in a team and communicate technical concepts clearly.
Added bonus if you have
- Experience deploying machine learning models in production environments.
- Exposure to CI/CD pipelines and version control systems like GitHub.
- Knowledge of data visualization tools such as Power BI or Tableau.
- Interest or experience in the automotive industry.
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