Senior Data Engineer

Ford Motor Company

Senior Data Engineer developing machine learning models for predictive maintenance and anomaly detection at Ford. Collaborating cross-functionally to drive innovations in smart manufacturing.

Posted 6/9/2026full-timeRedford • Missouri • 🇺🇸 United StatesSenior💰 $85,400 - $192,900 per yearWebsite

Tech Stack

Tools & technologies

BigQueryCloudDockerGoogle Cloud PlatformIoTKubernetesPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

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 (sensor data, PLC logs) to model deployment and monitoring using GCP and Python.
Statistical Analysis: Apply rigorous statistical methods to identify patterns in manufacturing data that correlate with vehicle quality or equipment downtime.
Cross-Functional Collaboration: Partner with Product and Engineering teams to translate manufacturing pain points into technical requirements and deliver user-centric data products.
Technical Leadership: Act as a subject matter expert within ATP, conducting code reviews, mentoring junior scientists, and staying at the forefront of AI/ML research in the industrial space.
Scalability: Ensure models are optimized for production environments, moving from localized pilots to global plant-wide deployments.
Data Strategy: Work with data engineering to improve data collection protocols and sensor telemetry quality from the plant floor.

Requirements

What you’ll need

Education: Requires a bachelor’s or foreign equivalent degree 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.
Experience: 5+ years of professional experience in a Data Science role, with a proven track record of deploying models into production environments.
Technical Stack:
Proficiency in Python (R and SQL are also highly valued).
Expertise in machine learning frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost, and LightGBM.
Experience working within Google Cloud Platform (GCP) (Vertex AI, BigQuery, Dataflow).
Domain Knowledge: Previous experience with time-series analysis, industrial IoT data, or manufacturing quality systems.
Preferred Requirements:
Advanced Degree: PhD in a relevant field.
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 (e.g., plant managers and design leads).
Problem-Solving: A "product-first" mindset—focusing on the business impact of the model rather than just its accuracy metrics.

Benefits

Comp & perks

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 and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
A generous schedule of paid holidays, including the week between Christmas and New Year's Day
Paid time off and the option to purchase additional vacation time.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningpredictive maintenanceanomaly detectioncomputer visionstatistical analysisPythonRSQLdeep learningtime-series analysis

Soft Skills

cross-functional collaborationtechnical leadershipcommunicationproblem-solving

Certifications

bachelor's degreemaster's degreePhD