7 days ago
Base Salary
$158k - $237k/yr
Responsibilities
- Design and productionize forecasting, anomaly detection, driver analysis, segmentation, recommendation, and other machine learning capabilities.
- Develop generative AI and large language model solutions using retrieval-augmented generation, semantic search, structured outputs, tool integration, and agent workflows.
- Create evaluation standards covering accuracy, relevance, groundedness, explainability, consistency, performance, cost, and business value.
- Build reusable data pipelines, analytical data models, features, semantic models, and governed data products.
- Implement data contracts, lineage, validation, reconciliation, quality controls, and consistent business definitions across systems and applications.
- Build services and platform capabilities to deploy, integrate, monitor, and scale AI and machine learning solutions.
- Apply automated testing, continuous integration and delivery, model monitoring, data-drift detection, observability, security, and lifecycle management.
- Partner with business, data, application, cloud, security, and architecture teams to move AI capabilities into supported production use.
- Establish reusable engineering standards, communicate risks and limitations, lead complex initiatives, and mentor analysts and engineers.
Requirements
- Bachelor’s degree desired in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related technical or quantitative field, with equivalent professional experience considered.
- Five or more years of related experience.
- Advanced experience with Python and SQL, modern data platforms such as Snowflake or Databricks, statistical and machine learning methods, API development, and cloud platforms such as Azure.
- Preferred experience with Azure Machine Learning, Microsoft Foundry, Azure OpenAI, MLflow, Docker, FastAPI, model operations, generative AI, vector search, and data observability.
- Certification is required in some areas.
- Demonstrated ability to lead complex technical initiatives, exercise strategic autonomy, influence technical and executive decisions, and mentor less experienced staff.
Benefits
- The role requires office presence at least five days per week in Dallas, Texas, with no relocation offered.
- Regular full-time schedule of 40 hours per week.
- Medical, dental, and vision coverage.
- 401(k) plan and tuition reimbursement.
- Paid time off, including at least 23 vacation days annually, nine company-designated holidays, paid parental leave, and paid caregiver leave.
- Additional sick leave may be available beyond statutory requirements.
- Adoption reimbursement, short- and long-term disability benefits, life and accidental death insurance.
- Supplemental critical illness, accident hospital indemnity, and group legal programs.
- Employee assistance and wellness programs.
- Employee discounts of up to 50% on eligible AT&T mobility plans, accessories, internet, fiber where available, and phone services.
Categories
Data EngineeringML Engineering