Machine Learning Engineer

Dow’s Enterprise Data & Analytics organization is hiring a Machine Learning Engineer to design, develop, and deploy machine learning systems on Azure Databricks. The role partners across teams to deliver dependable, maintainable AI/ML capabilities and to advance MLOps best practices.

Role Location and Work Arrangement

Onsite roles in Houston, TX, Midland, MI, or Champaign, IL.

Responsibilities

• Design and implement pipelines and workflow infrastructure for new AI/ML solutions supporting online, batch, or real-time inference requirements.
• Deploy and monitor machine learning models in production using Databricks Model Registry, Databricks Jobs, and Databricks Workspace.
• Collaborate frequently with data engineers, DevOps/platform engineers, data scientists, and domain experts within a comprehensive MLOps framework to support performance, reliability, and maintainability.
• Work with application development teams to enable seamless integrations.
• Apply proficiency across ML frameworks including scikit-learn, TensorFlow, PyTorch, and Keras, plus distributed frameworks such as Spark MLlib and Ray.
• Conduct data analysis and feature engineering, perform model selection, execute hyperparameter optimization, and evaluate models using Databricks MLflow, Delta Lake, SQL Analytics, and other tools throughout the end-to-end ML lifecycle.
• Research and implement new machine learning techniques and methods using Databricks, staying current with trends and technologies.
• Document and communicate results and insights to stakeholders through Databricks notebooks and Databricks dashboards.
• Understand and implement IT security policies as part of solution design.
• Follow and promote organizational machine learning and MLOps standards using Databricks and Azure DevOps.

Minimum Qualifications

• Bachelor’s degree (or 8 years relevant experience), with relevant military experience at an E6 rank / Petty Officer 2nd Class or higher also accepted.
• At least 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 is available, including for any U.S. permanent residency (green card) process.

Preferred Qualifications

• Degree in computer science, engineering, mathematics, statistics, data science, or a 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 ML concepts to technical and non-technical audiences using Databricks notebooks and dashboards.
• Ability to work independently and collaboratively in a fast-paced environment.
• Curiosity and passion for learning new machine learning skills and technologies using Databricks.
• Strong knowledge of data modeling, data warehousing, and ETL processes.
• Experience designing and deploying into production both traditional and generative AI systems.
• Proficiency in SQL and experience with big data technologies such as Apache Spark and Hive.
• Experience working within Azure Machine Learning.
• Experience containerizing and deploying ML models to Azure Kubernetes Service.
• Experience with Azure Data Factory, Azure Data Lake Storage Gen2, and other Azure services.
• Multi-application and cross-platform design experience.
• Understanding of data lakehouse platform design and associated workflows.
• Ability to thrive in challenging situations and solve complex problems.
• Ability to manage own work effort across multiple projects with limited supervision.
• Interest in emerging technologies and ability to quickly learn and apply cutting-edge offerings to achieve business objectives.

Technologies and Tools

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, REST APIs.

Benefits

• Equitable and market-competitive base pay and bonus opportunity across global markets, with locally relevant incentives.
• Benefits and programs to support physical, mental, financial, and social well-being.
• Competitive retirement program that may include company-provided benefits, savings opportunities, financial planning, and educational resources.
• Employee stock purchase programs (availability varies by location).
• Student Debt Retirement Savings Match Program (U.S. only).
• Robust medical and life insurance packages with coverage options.
• Learning and development opportunities through training and mentoring, work experiences, community involvement, and team building.
• Workplace culture that enables role-based flexibility to support productivity and balance personal needs.
• Competitive yearly vacation allowance.
• Paid time off for new parents (birthing and non-birthing, including adoptive and foster parents).
• Paid time off to care for family members who are sick or injured.
• Paid time off to support volunteering and Employee Resource Group (ERG) participation.
• Wellbeing Portal for all Dow employees.
• On-site fitness facilities (availability varies by location).
• Employee discounts for online shopping, cinema tickets, gym memberships, and more.
• Transportation allowance (availability varies by location).
• Meal subsidiaries/vouchers (availability varies by location).
• Carbon-neutral transportation incentives (for example, bike to work; availability varies by location).

Additional Notes

• No relocation assistance is offered for this position.
• No people leadership responsibility. This role is an Independent Contributor; you may coach and mentor junior resources.