Machine Learning Engineer

dow; Houston (TX); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equitable base pay & bonus opportunity

Comprehensive medical & life insurance

Employee stock purchase program

Paid time off and family leave

Retirement & financial planning

Job summary

Dow is seeking a Machine Learning Engineer to design, develop, and deploy production-ready ML systems on site in Houston, TX (also in Midland, MI or Champaign, IL). You will build end-to-end ML workflows, deploy models, and maintain operations with robust MLOps using Azure Databricks, MLflow, and related tools.

You will collaborate with data engineering, DevOps, and software teams to deliver reliable AI capabilities while adhering to IT security policies and governance.

Qualifications

• Bachelor's degree or 8 years of relevant experience, or military E6 or higher.
• At least 3 years in ML, data science, or related field.
• Ability to work legally in the United States; no visa sponsorship provided.

Responsibilities

• Design and implement end-to-end ML pipelines for online, batch, and real-time inference.
• Deploy and monitor ML models in production using Databricks tools.
• Collaborate with data engineers, DevOps, data scientists, and developers to deliver scalable AI/ML solutions.
• Work with application teams to enable integration and secure designs.
• Document results and insights using Databricks notebooks and dashboards.

Skills

End-to-end ML workflows

Model deployment

MLOps practices

Collaboration across teams

Education

Bachelor's degree

Tools

Azure Databricks

Databricks MLflow

Delta Lake

SQL Analytics

Model Registry

Databricks Jobs/Workspace

TensorFlow

PyTorch

scikit-learn

Keras

Spark MLlib

Ray

Azure DevOps

Job description

Dow’s Enterprise Data & Analytics organization is seeking a Machine Learning Engineer to design, develop, and deploy machine learning systems across online, batch, and real-time use cases. The role is onsite in Houston, TX; Midland, MI; or Champaign, IL and focuses on building and maintaining production-ready solutions using Azure Databricks and associated MLOps tooling.

Role Overview

In this position, you will engineer end-to-end machine learning workflows, deploy models to production, and support reliable operations through monitoring and strong MLOps practices. You will collaborate with cross-functional teams, including data engineering, DevOps/platform engineering, data science, and application development, to deliver performant and maintainable AI/ML capabilities. Work includes documenting results and insights for stakeholders using Databricks notebooks and dashboards, while aligning designs with IT security policies.

Key Responsibilities

• Design and implement pipelines and workflow infrastructure for new AI/ML solutions supporting online, batch, and real-time inference.
• Deploy and monitor machine learning models in production using Databricks Model Registry, Jobs, and Workspace.
• Collaborate within a comprehensive MLOps framework with data engineers, DevOps/platform engineers, data scientists, and domain experts to support performance, reliability, and maintainability.
• Work closely with application development teams to support seamless integration.
• Use and apply machine learning frameworks including scikit-learn, TensorFlow, PyTorch, Keras, and distributed frameworks such as Spark MLlib and Ray.
• Perform data analysis and feature engineering; support model selection, hyperparameter optimization, and evaluation across the end-to-end ML lifecycle using Databricks MLflow, Delta Lake, SQL Analytics, and other tools.
• Research and implement new machine learning techniques and methods using Databricks while staying current on trends and technologies.
• Document and communicate machine learning results and insights to stakeholders using Databricks notebooks and dashboards.
• Understand IT security policies and incorporate them into new solution designs.
• Follow and promote organizational machine learning and MLOps best practices and standards using Databricks and Azure DevOps.

Required Qualifications

• A minimum of a Bachelor’s degree, or 8 years of relevant experience, or relevant military experience at an E6 rank / Petty Officer 2nd Class or higher.
• 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 for this position, including for any U.S. permanent residency (green card) process.

Technologies

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 supporting 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 a variety of coverage options.
• Training and mentoring opportunities through learning experiences, team building, community involvement, and growth support.
• Workplace culture supporting role-based flexibility to maximize personal productivity and balance 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 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 subsidies/vouchers (availability varies by location).
• Carbon-neutral transportation incentives such as bike to work (availability varies by location).

Preferred Qualifications

• Degree in computer science, engineering, mathematics, statistics, data science, or a related field.
• Proficiency in Python and one or more machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience developing and deploying machine learning 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 machine learning concepts and results to technical and non-technical audiences using Databricks notebooks and dashboards.
• Ability to work independently and collaboratively in a fast-paced, dynamic 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 little supervision.
• Interest in emerging technologies with the ability to quickly learn and apply cutting-edge offerings to achieve business objectives.

Additional Notes

• No relocation assistance is offered for this position.
• This position does not have people leadership responsibility. It is an Independent Contributor role; however, you may coach and mentor junior resources.