7 days ago
Dallas, TX, USAMid Level
Base Salary
$89k - $133k/yr
Responsibilities
- Build and maintain production machine learning capabilities spanning feature engineering, training, evaluation, deployment, and model inference.
- Design and build agentic AI systems involving tool use, orchestration, memory, evaluation harnesses, and production observability.
- Own monitoring and alerting for model performance, data drift, and prediction quality, including end-to-end on-call incident response.
- Collaborate with Data Scientists to convert experimental work into tested, maintainable, production-grade code.
- Partner with engineering and product teams to deliver mission-critical machine learning and AI capabilities.
- Improve the latency, throughput, cost, reliability, and operational health of production ML and agentic systems.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.
- At least 2 years of professional experience in software engineering, systems engineering, machine learning engineering, or AI engineering.
- Experience building, deploying, and supporting production applications in an enterprise environment.
- Proficiency in a programming language such as Python, Java, or C#.
- Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
- Working knowledge of distributed databases, caching systems, and vector databases for high-throughput, low-latency workloads.
- Strong communication skills for technical and non-technical audiences.
- Experience on a fast-paced, collaborative, agile team in a product-oriented organization.
- Preferred experience with AI coding agents and human verification of agent-generated work.
- Preferred MLOps experience including experiment tracking, model registries, reproducible training, and CI/CD or automated ML retraining.
- Preferred experience with MLflow, Azure ML, SageMaker, Kubeflow, or equivalent tools.
- Preferred experience with model serving platforms and real-time inference.
- Preferred experience with microservices, containers, Kubernetes, service-to-service APIs, and distributed architectures.
Benefits
- The role is based in Richmond, Virginia with onsite work 4 days per week, or Plano, Texas with onsite work 2 days per week.
- Full-time associates receive paid sick, vacation, and holiday time, subject to employment classification and applicable policy.
- Full-time hourly or commission/incentive-eligible associates can earn up to 48 hours of sick time annually and 80–200 hours of vacation after a 90-day waiting period, depending on tenure.
- Full-time salaried associates receive paid time away as needed for sick leave, vacation, bereavement, jury duty, holidays, and floating holidays, subject to manager approval.
- Eligible associates receive pay for six scheduled holidays and one floating holiday, with holiday premium pay when business needs require work on a scheduled holiday.
- Reasonable accommodation is available upon request for completing the application.
Tech Stack
Categories
About CarMax
We're fueled by a common goal: creating an iconic car-buying experience. We make car-buying fair, accessible, and joyful for all. We are committed to making progress in how we positively impact our society, now and in the future. Above all, we care about people. We are committed to putting people first, including our associates, customers, and communities. Spark positive change alongside us. Here’s your chance to leave a mark. Find the purpose, tools, and resources to go for greatness with teammates by your side. We offer benefits and resources to help make your best life happen. Professional growth and limitless opportunities await. There's no better place to be.