Senior Data Engineer

Overview

• Job Type: Full time
• Work Type: Hybrid

Responsibilities

• Design and deploy advanced machine learning models for predictive maintenance, anomaly detection, and computer vision driven quality assurance.
• Architect data pipelines that span data ingestion (sensor data, PLC logs) through model deployment and monitoring, utilizing Google Cloud Platform and Python.
• Apply rigorous statistical methods to reveal patterns in manufacturing data that relate to vehicle quality or equipment downtime.
• Collaborate with Product and Engineering teams to translate manufacturing pain points into technical requirements and deliver data products focused on user needs.
• Serve as a subject matter expert within ATP, perform code reviews, mentor junior scientists, and stay current with AI/ML research in industrial settings.
• Optimize models for production environments to scale from pilots to plant-wide deployments.
• Partner with data engineering to improve data collection protocols and sensor telemetry quality from the plant floor.

Requirements

• Education: 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.
• 5+ years of professional experience in a Data Science role with a demonstrated track record of deploying models to production.
• Proficiency in Python (R and SQL are highly valued).
• Expertise in 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.
• 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 ML, containerization (Docker/Kubernetes), and model monitoring tools.
• Strong communication skills with the ability to explain complex mathematical concepts to non-technical stakeholders.
• Problem-solving mindset with a product-first focus on the business impact of the model.

Technologies

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

Benefits

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