Machine Learning Engineer (W2)

We Miracle Software Systems is looking for the Machine Learning Engineer on W2/Full-time to our direct client at Dearborn, MI location

Experience required: 8 years

Only W2/Full-time

Role: Machine Learning Engineer

Location: Dearborn, Michigan

Duration: 12 Months

Skills: Python, GCP, Git (GitHub), SonarQube, Cycode, FOSSA, Kubernetes, OpenShift, DataProc, Spark/PySpark, or Airflow, Tekton or Terraform, Docker or Kubernetes, Atlassian (Jira, Confluence)

Position Description:

We are seeking an experienced Machine Learning Engineer to design, implement, and maintain robust analytics pipeline solutions. These solutions will support the analysis, modeling, and prediction of upstream and downstream auction prices, directly benefiting the Business and Sales Planning Analytics (BSPA) Used Vehicle Analytics team and its customers. The ideal candidate will excel at developing ML/Software Engineering Solutions, performing DevSecOps, and collaborating with cross-functional teams (including ML Engineers, Data Scientists, and Data Engineers) to improve processes and drive business performance. Responsibilities: • Develop, build and maintain infrastructure required for machine learning, including data pipelines, model deployment platforms, and model monitoring. • Develop and maintain tools and libraries to support the development and deployment of machine learning models. • Automate machine learning workflows using DevSecOps principles and practices.

Skills Required:

• 8 years of experience in developing and deploying machine learning models in a production environment. • 3 years of experience in programming with Python • 3 years of hands-on experience utilizing Google Cloud Platform (GCP) services, including BigQuery and Google Cloud Storage to efficiently manage and process large datasets, as well as Cloud Composer and/or Cloud Run. • Experience with version control systems like GitHub for managing code repositories and collaboration. • 3 years of experience with code quality and security scanning tools, such as, SonarQube, Cycode and FOSSA. • 3 years of experience with data engineering tools and technologies, such as, Kubernetes, Container-as-a-Service (CaaS) platforms, OpenShift, DataProc, Spark (with PySpark) or Airflow. • Experience with CI/CD practices and tools, including Tekton or Terraform, as well as containerization technologies like Docker or Kubernetes. • Excellent problem-solving and analytical skills, with a focus on data-driven solutions. • Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud Platform. • Familiarity with Atlassian project management tools (e.g., Jira, Confluence) and agile practices.

Skills Preferred:

• Proven ability to thrive in dynamic environments, managing multiple priorities and delivering high-impact results even with limited information. • Exceptional problem-solving skills, a proactive and strategic mindset, and a passion for technical excellence and innovation in data engineering. • Demonstrated commitment to continuous learning and professional development. • Familiarity with machine learning libraries, such as TensorFlow, PyTorch, or Scikit-learn • Experience with MLOps tools and platforms.

Experience Preferred:

5 years of experience in the automotive industry, particularly in auto remarketing and sales