Machine Learning Engineer MLOps & Cloud Data Engineering

Job Title

Senior Machine Learning Engineer MLOps & Cloud Data Engineering

Overview / Summary

We are seeking a Senior Machine Learning Engineer with expertise in MLOps, cloud data engineering, and scalable machine learning pipelines to join our team working onsite in Dearborn, MI. The role focuses on building and optimizing ML data pipelines, supporting AI/ML initiatives, enhancing DevOps capabilities, and delivering reliable data solutions in a cloud environment. This position requires strong collaboration, communication, and technical problem-solving skills within an agile development environment.

Key Responsibilities

• Build scalable and robust ML data pipelines in the cloud to process large volumes of data.
• Optimize existing ML solutions for performance, security, reliability, and cost-effectiveness.
• Utilize continual learning methods to improve model performance.
• Develop analytical data products using streaming and batch ingestion patterns on Google Cloud Platform.
• Build and maintain data pipelines for monitoring data quality and analytical model performance.
• Maintain infrastructure using Terraform and support CI/CD development practices.
• Collaborate with analytics stakeholders to streamline data acquisition, processing, and presentation.
• Implement and promote enterprise data governance standards, including data protection, sharing, reuse, and quality.
• Enhance and maintain DevOps capabilities of the data platform.
• Continuously improve data pipelines, products, and infrastructure for scalability and operational efficiency.
• Work within an agile product team using Test Driven Development (TDD), CI/CD, and frequent code delivery practices.
• Address code quality and security issues throughout the development lifecycle.
• Perform data mapping, data lineage activities, and document information flows.
• Monitor production pipelines and provide production support in accordance with SLAs.
• Analyze connected data to support product development and operational improvements.
• Identify data quality and feature issues and collaborate with stakeholders on resolution.
• Demonstrate strong technical communication skills and advocate for well-designed solutions.
• Stay current with modern data engineering and MLOps practices and contribute to technical improvements.

Required Qualifications

• Bachelor s degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field.
• 6+ years of professional experience with a Bachelor s degree OR 4+ years with a Master s degree.
• Experience in data engineering, data product development, and software product launches.
• Proficiency in at least three of the following: Java, Python, Spark, Scala, SQL.
• 3+ years of cloud data/software engineering experience building scalable batch and streaming data pipelines.
• Experience with cloud data warehouses such as Google BigQuery, Amazon Redshift, or Azure Synapse Analytics.
• Experience with workflow orchestration tools such as Airflow.
• Experience with relational databases including MySQL, PostgreSQL, or SQL Server.
• Experience with real-time streaming platforms such as Apache Kafka or Google Cloud Platform Pub/Sub.
• Experience with microservices architecture and REST APIs.
• Experience with DevOps tools including GitHub, Git, Terraform, Docker, Tekton, or GitHub Actions.
• Experience with project management tools such as Jira.
• Strong understanding of Google Cloud Platform (Google Cloud Platform).
• Experience with TensorFlow and machine learning operations (MLOps).
• Strong communication and technical presentation skills.
• Experience working in Agile software development environments.

Preferred Qualifications

• Master s or Ph.D. in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field.
• Experience with ML model development and/or MLOps.
• Experience contributing to open-source data/software engineering projects.
• Experience architecting cloud infrastructure and handling application migrations/upgrades.
• Google Cloud Platform Professional Certifications.
• Experience with data modeling, data mining, and database design.
• Strong troubleshooting and analytical skills.
• Ability to mentor and guide junior team members.
• Knowledge of telematics or connected data environments.

#LI-Onsite #LI-GL1 #MLOps #Hiring #NowHiring #MachineLearningEngineer