Senior Data Engineer

The Senior Data Engineer role at Ford Motor Company in Redford, MI (hybrid) focuses on guiding the end-to-end data science lifecycle within manufacturing. The position involves designing machine learning models and scalable data pipelines, with strong cross-functional collaboration and technical leadership.

Overview

Location: Redford, MI, hybrid work arrangement. Compensation: USD 85,400 to 192,900 per year. Employment type: Full time; Work type: Hybrid. Education requirements include a bachelor's or foreign equivalent in computer science, information technology, or a technology-related field, plus a Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field. An advanced degree such as a PhD in a relevant field is also specified. Minimum experience required: 5 years.

Responsibilities

• Model Development: Design and implement advanced machine learning models for predictive maintenance, anomaly detection, and computer vision-based quality control.
• End-to-End Pipeline Construction: Architect data pipelines from ingestion of sensor data and PLC logs to model deployment and monitoring using GCP and Python.
• Statistical Analysis: Apply rigorous statistical methods to uncover patterns in manufacturing data that correlate with vehicle quality or equipment downtime.
• Cross-Functional Collaboration: Partner with Product and Engineering teams to translate manufacturing challenges into technical requirements and deliver user-centric data products.
• Technical Leadership: Serve as a subject matter expert within ATP, conduct code reviews, mentor junior scientists, and stay at the forefront of AI and ML research in industrial applications.
• Scalability: Optimize models for production environments, advancing from localized pilots to global plant-wide deployments.
• Data Strategy: Collaborate with data engineering to improve data collection protocols and sensor telemetry quality from the plant floor.

Requirements

• Education: Bachelor’s degree or foreign equivalent in computer science, information technology, or a technology-related field; Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field; Advanced degree: PhD in a relevant field.
• Experience: 5+ years of professional experience in a Data Science role with a proven track record of deploying models into production.
• Technical Proficiency: Strong Python skills; proficiency in R and SQL is highly valued.
• Machine Learning Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost, and LightGBM.
• Cloud Experience: Google Cloud Platform including Vertex AI, BigQuery, Dataflow.
• Domain Knowledge: Time-series analysis, industrial IoT data, or manufacturing quality systems.
• Deep Learning: Experience with Computer Vision (CNNs) for automated inspection or Transformers for complex sequence modeling in sensor data.
• MLOps: Familiarity with CI/CD for machine learning, containerization (Docker/Kubernetes), and model monitoring tools.
• Communication: Ability to explain complex mathematical concepts to non-technical stakeholders such as plant managers and design leads.
• Problem-Solving: A product-first mindset focusing on business impact of the model beyond mere accuracy metrics.

Technologies

• Programming and analytics: Python, R, SQL
• ML frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost, LightGBM
• Cloud and data tools: Google Cloud Platform (Vertex AI, BigQuery, Dataflow)
• DevOps and containers: Docker, Kubernetes

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members, along with management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• Generous holidays including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time