Jobs · Information Technology · Virginia

Sr. Engineer, AI & ML

CarMax · Richmond, VA · 3 mo ago
On-siteInformation Technology$120k–$180k/yrFull-time

About the role

At CarMax, a Senior Engineer, Artificial Intelligence is a technologist with domain-specific expertise in Generative AI, able to address advanced concepts and feature designs for hosting deep-learning models that generate content with processes and tools for testing, evaluating, and analyzing the AI system. As a member of the GenAI team, you will have a direct impact on improving the performance of our business through machine learning and Generative AI system implementations that drive CarMax’s iconic omni-channel customer experience.

Responsibilities

  • Provide reliable and scalable machine-learning capabilities across the organization.
  • Closely partner with Data Scientists to design and productionalize machine learning models, including testing and monitoring of the applications and front-end experiences.
  • Develop tools and technology, learning quickly from our spirit of experimentation.
  • Ensure customers can buy the vehicles they want in a way that is right for them!

Requirements

  • 5+ years’ software-engineering experience in an enterprise-level environment
  • 2+ years’ experience designing and developing on distributed architectures (microservices, Kubernetes, etc.)
  • 2+ years leading the end-to-end design and development of scalable services to be consumed by the enterprise, including monitoring and production support
  • Proficient in the Python programming language
  • 2+ years’ experience building enterprise-level solutions with Microsoft Azure or equivalent cloud technologies
  • Experience in DevOps practices, testing frameworks, and CI/CD
  • Excellent communication skills, adapting to various audience types
  • Experience on a fast-paced, highly collaborative agile team within a Product-oriented organization
  • Ability to positively influence team norms, culture, and technical vision
  • Bachelor’s Degree in Computer Science or related Technology field or equivalent experience

Preferred Qualifications

  • Master's in Computer Science, Engineering, Decision Sciences or equivalent area
  • Proficient in an object-oriented programming language (i.e. C#, Java)
  • Proficient in writing production level code in python (services, applications, etc.)
  • Experience in machine-learning and/or AIaaS with demonstrated knowledge or projects
  • Familiarity with MLOps and industry-standard machine-learning Python libraries
  • Enthusiastic about the vision of building an augmented algorithmic organization
  • Model Development and Deployment (MLFlow, Azure ML, Sage Maker, or others)
  • Data Science Libraries and Algorithms (TensorFlow, Scikit, PyTorch, etc)

Work Location and Arrangement

This role will be based out of the CarMax Midtown office, Richmond VA or CarMax Technology Hub, Plano TX and have a Hybrid work arrangement.

  • Associates based in Richmond work onsite 5 days per week.
  • Associates based in Plano work onsite 2 days per week.

Pay

The annual salary for this position is: $120,000.00 - $180,000.00 May be eligible for bonus and equity.

Benefits

Except as otherwise required by state law, CarMax Associates are entitled to the following paid sick, vacation, and holiday time.

  • Associates that are considered full-time hourly or commission/incentive eligible:
  • To earn up to 48 hours of sick time per year accrued on a per pay period basis and between 80 hours and 200 hours per year of vacation time after a 90 day waiting period depending on years of continuous service with the Company.
  • For 8 hours of pay for each of a total of 6 paid scheduled holidays per year plus 1 floating holiday. If such an Associate does work on a scheduled holiday due to business need, they are eligible for Holiday Premium Pay.
  • Associates considered full-time salaried are entitled to paid time away with no specified limit as needed for sick, vacation, bereavement, jury duty, holidays, floating holiday, etc. subject to manager approval.

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