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.
