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.