Machine Learning Engineer

Dow is hiring a Machine Learning Engineer within its Enterprise Data & Analytics organization, with an onsite location in Houston, TX, Midland, MI, or Champaign, IL. In this role, you will design, develop, and deploy machine learning systems on Azure Databricks, apply MLOps best practices, and collaborate across teams to help deliver performant, reliable, and maintainable AI and ML solutions.

Why Dow

• Equitable, market-competitive base pay with bonus opportunity across global markets, plus locally relevant incentives
• Benefits and programs supporting physical, mental, financial, and social well-being
• Competitive retirement program that may include company-provided benefits, savings opportunities, financial planning, and educational resources
• Robust medical and life insurance packages with coverage options
• Training and mentoring through learning opportunities, work experiences, community involvement, and team building
• Role-based flexibility designed to support productivity and balance personal needs
• Generous paid time off, including time off for new parents (birthing and non-birthing, including adoptive and foster parents) and to care for sick or injured family members
• Wellbeing Portal for all Dow employees
• On-site fitness facilities where available, plus employee discounts and other location-dependent perks

What you’ll do

• Design and implement pipelines and workflow infrastructure for new AI/ML solutions requiring online, batch, or real-time inference
• Deploy and monitor models in production using Databricks Model Registry, Jobs, and Workspace
• Collaborate frequently with data engineers, DevOps/platform engineers, data scientists, and domain experts to deliver ML solutions that are performant, reliable, and maintainable under an MLOps framework
• Work with application development teams to support seamless integrations
• Build with multiple ML frameworks including scikit-learn, TensorFlow, PyTorch, and Keras, and distributed approaches such as Spark MLlib and Ray
• Drive the end-to-end ML lifecycle through data analysis, feature engineering, model selection, hyperparameter optimization, and evaluation using Databricks MLflow, Delta Lake, and SQL Analytics (and other tools)
• Research and implement new machine learning techniques using Databricks while staying current on trends and technologies
• Document and communicate results using Databricks notebooks and dashboards
• Incorporate IT security policies into solution design
• Follow and promote ML and MLOps best practices across the organization using Databricks and Azure DevOps

Required qualifications

• A Bachelor’s degree, or 8 years relevant experience, or relevant military experience at an E6 rank/Petty Officer 2nd Class or higher
• Minimum 3 years of experience developing solutions in machine learning, data science, or a related field
• Ability to work legally in the United States (no visa sponsorship/support available, including for any U.S. permanent residency/green card process)

Technologies you’ll work with

Azure Databricks, Databricks Model Registry, Databricks Jobs, Databricks Workspace, scikit-learn, TensorFlow, PyTorch, Keras, Spark MLlib, Ray, Databricks MLflow, Delta Lake, SQL Analytics, Databricks notebooks, Databricks dashboards, Azure DevOps, Azure Data Factory, Azure Workflows, Functions, Logic Apps, Azure SQL, CI/CD, IaC, Event Hubs, Kafka, SQL Server, Cosmos DB, Neo4j, OAuth, RBAC, Apache Spark, Hive, Azure Machine Learning, Azure Kubernetes Service, Azure Data Lake Storage Gen2, SQL, and REST APIs.

Preferred qualifications

• Degree in computer science, engineering, mathematics, statistics, data science, or related field
• Proficiency in Python and one or more ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Experience developing and deploying ML models and pipelines on Databricks using Databricks MLflow, Delta Lake, SQL Analytics, Model Registry, Jobs, and Workspace
• Strong knowledge of machine learning concepts, techniques, and algorithms
• Ability to perform data analysis, feature engineering, model selection, optimization, and evaluation using Databricks
• Ability to communicate complex concepts and results to technical and non-technical audiences using Databricks notebooks and dashboards
• Interest in learning and applying new machine learning skills and technologies using Databricks
• Strong knowledge of data modeling, data warehousing, and ETL processes
• Experience designing and deploying traditional and generative AI into production
• Proficiency in SQL and experience with big data technologies such as Apache Spark and Hive
• Experience with Azure Machine Learning and containerizing/deploying to Azure Kubernetes Service
• Experience with Azure Data Factory and Azure Data Lake Storage Gen2
• Multi-application and cross-platform design experience; understanding of data lakehouse platform design and associated workflows
• Ability to solve complex problems in challenging situations and manage own work effort across multiple projects with little supervision
• Interest in emerging technologies and quick learning to achieve business objectives

Additional notes: This position does not offer relocation assistance. It is an Independent Contributor role with no people leadership responsibility, though you may coach and mentor junior resources.