Machine Learning Engineer

Stanley Martin Homes•Reston, VA

14h•Hybrid

About The Position

At Stanley Martin Homes, we believe your work should have a purpose. With us, it truly does. Our success starts with our people, and we are proud to foster a culture where every team member is valued and supported. At Stanley Martin Homes, you will work alongside passionate, knowledgeable professionals who are committed to doing the right thing, delivering exceptional homebuyer experiences, and putting homebuyers first. Stanley Martin Homes is one of the largest 25 homebuilders in the United States and it has been consistently one of the fastest growing. We are proud of the people-first culture that makes it possible. If you are ready to build a meaningful career and help families find the place they will call home, we would love to connect with you. Join our team and build a career that you will be proud of. Explore Opportunities Today The Machine Learning Engineer will design, develop, and operationalize machine learning models and data pipelines that deliver actionable insights across the organization. The Machine Learning Engineer will collaborate with data engineers, data scientists, BI developers, and business stakeholders to translate complex data problems into production-ready ML solutions.

Requirements

Bachelor's degree in Computer Science, Data Science, Mathematics, Engineering, or a related field; equivalent experience considered.
3+ years of professional experience in machine learning, data science, or a related technical role (internships and graduate research applicable).
Proficiency in Python; experience with R or Scala is a plus.
Solid understanding of machine learning algorithms, statistical modeling techniques, and model evaluation methods.
Experience with databases such as BigQuery, Snowflake, or SQL Server, along with strong SQL skills.
Experience working with large-scale datasets and distributed computing tools (e.g., Snowpark, Spark, Hadoop).
Demonstrated ability to translate business requirements into ML problem formulations and deployable solutions.
Strong analytical and problem-solving skills with high attention to detail and data accuracy.
Effective communication and collaboration skills; ability to convey technical concepts to both technical and non-technical stakeholders.
Self-motivated, detail-oriented, and eager to learn new technologies and methodologies.
Willingness to work in a hybrid environment (3 days per week onsite).

Nice To Haves

Experience working on multi-team, cross-disciplinary projects in a production ML environment.
Exposure to Marketing, Sales, or CRM analytics concepts (e.g., lead scoring, churn prediction, campaign attribution, sales pipeline forecasting).
Familiarity with MLOps practices including model versioning, CI/CD pipelines for ML, and automated retraining workflows.
Experience with hyperparameter optimization strategies and experiment tracking tools (e.g., MLflow, Weights & Biases).
Knowledge of natural language processing (NLP) or computer vision techniques is a plus.
Familiarity with data warehousing concepts and dimensional modeling.
Interest in AI-enhanced analytics, large language models (LLMs), and conversational AI tooling.
Industry exposure to residential real estate, construction, consumer behavior, or digital marketing is helpful.

Responsibilities

Design, develop, and deploy machine learning models to support business use cases across sales, marketing, operations, and customer experience.
Build and maintain scalable data pipelines for data ingestion, transformation, and feature engineering using Python and cloud-based tools.
Collaborate with data engineers and BI developers to integrate ML outputs into dashboards, reporting layers, and downstream systems.
Perform exploratory data analysis (EDA) to understand data characteristics, identify patterns, and inform model development.
Develop and implement model evaluation frameworks, including testing, validation, and performance monitoring in production.
Optimize and tune machine learning models and hyperparameters to meet performance goals and business requirements.
Package and deliver models for deployment in cloud environments, ensuring reproducibility and version control.
Contribute to ML codebase development and code reviews, following best practices in software engineering and MLOps.
Participate in technical discussions, solution design, and requirements gathering with cross-functional stakeholders.
Monitor deployed models for drift, performance degradation, and data quality issues; implement retraining pipelines as needed.
Stay current on emerging ML frameworks, tools, and industry trends; apply learnings to improve team capabilities.
Contribute to presentations and documentation summarizing model results, methodologies, and recommendations for technical and non-technical audiences.

Benefits

Access to competitively priced, high-quality health care options through Aetna, MetLife and EyeMed, along with employer-paid Short Term and Long Term disability, basic life and AD&D insurance (including employee-paid life, Legal Resources, and Aflac supplemental options)
Plan for the future by investing in a 401(K), with up to $5K employer match, invest even more with our Health Savings Account (HSA)
Put your family first with benefits, including 3 weeks of paid parental leave and a Flexible Spending Account (FSA) for dependent care
12 weeks of paid maternity leave through our Short-Term Disability Plan
Receive well-rounded wellness benefits, including free and low-cost mental health resources and support services through our Employee Assistance Program
Continue your education with tuition and certification reimbursement
Rest and relax with 15 days of vacation (increases with tenure) and 6 days of paid sick leave
Protect yourself from identity theft or travel mishaps with our no-cost coverage
Receive great discounts on buying a Stanley Martin home and discounts with our partners in mortgage and title services as well as cell phone service through Verizon
Get access to your paycheck early with an advanced pay option through Dayforce Wallet
Support local charities that are important to you through our Giving Back Program; with up to $250 match, 8 hours leave and more