Data Jobs in Redford, MI

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2d ago

Senior Data Engineer

Ford Motor Company Redford, MI

Redford, MI

2d ago

$85k - $193k/yr Full time Senior Cloud Operations Data Analysis

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Job Description

Ford Motor Company offers a compelling compensation package for a Senior Data Engineer, with an annual salary range of USD 85,400 to 192,900 and a hybrid work arrangement in Redford, MI. The role centers on leading end-to-end data science work in manufacturing, designing scalable data pipelines and machine learning models, and providing technical leadership across cross-functional teams. The environment emphasizes collaboration, data-driven decision making, and tangible impact on vehicle quality and plant uptime. The benefits package includes robust medical coverage, flexible family support, parental leave and ramp-up programs, subsidized back-up child care, a vehicle discount program for employees and families, tuition assistance, active employee resource groups, paid time off for community service, a generous holiday calendar, and the option to purchase additional vacation time.

Overview

Job Type: Full time
Work Type: Hybrid
Location: Redford, MI

Responsibilities

Develop and deploy advanced machine learning models for predictive maintenance, anomaly detection, and computer vision based quality control.
Build end-to-end data pipelines from ingestion (sensor data, PLC logs) to model deployment and monitoring using Google Cloud Platform and Python.
Apply rigorous statistical methods to identify patterns in manufacturing data that correlate with vehicle quality or equipment downtime.
Collaborate with Product and Engineering teams to translate manufacturing challenges into technical requirements and deliver user focused data products.
Provide technical leadership within ATP, conduct code reviews, mentor junior scientists, and stay at the forefront of AI and ML research in industrial settings.
Ensure models are production-ready, scaling pilots to global plant deployments across facilities.
Partner with data engineering to improve data collection protocols and sensor telemetry quality from the plant floor.

Requirements

Bachelor’s degree or foreign equivalent in computer science, information technology, or a related technology field
Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related quantitative field
Minimum 5 years of professional experience in a Data Science role with a proven track record of deploying models in production
Proficiency in Python; knowledge of R and SQL is highly valued
Expertise with ML frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost, and LightGBM
Experience with Google Cloud Platform (Vertex AI, BigQuery, Dataflow)
Domain knowledge in time-series analysis, industrial IoT data, or manufacturing quality systems
PhD in a relevant field
Deep Learning experience with Computer Vision (CNNs) for automated inspection or Transformers for complex sequence modeling in sensor data
Experience with MLOps, including CI/CD for ML, containerization (Docker/Kubernetes), and model monitoring tools
Strong communication skills with the ability to explain complex mathematical concepts to non-technical stakeholders
Product-first mindset focused on business impact of the model rather than solely on accuracy metrics

Technologies

Python
R
SQL
PyTorch
TensorFlow
Scikit-learn
XGBoost
LightGBM
Google Cloud Platform (GCP)
Vertex AI
BigQuery
Dataflow
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 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

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