CarMax
Responsibilities:
Identify new opportunities for ML and AI solutions and build and cultivate relationships with leaders across the organization to foster those partnerships
Influence partners and stakeholders in Data Science and other teams across the organization to prioritize objectives and provide a comprehensive approach to solution recommendations that includes ROI, time to market, scalability as well as alternative recommendations
Communicate effectively with senior leadership to share progress, raise any roadblocks or impediments to delivery, and also spread awareness of your teams’ achievements
Create the strategic roadmap that will guide the direction and goals for the team, both in terms of individual project impacts but also overall standards for machine learning and AI utilization in the organization
Empower your direct reports to lead their teams by providing them with the resources, training, feedback, and a sounding‑board to be successful in their roles
Develop people through effective communication and ongoing feedback
Manage the budget of your area including budget planning and estimating costs of future development and tracking spend on an ongoing basis
Create an inclusive and engaging culture for a team of remote and hybrid engineers with varying levels of experience
Work through others to deliver resilient and scalable technology solutions that solve for complex business problems
Help drive the broader understanding of the use of machine learning and AI by interfacing with key roles in Operations, Legal, Security, and Technology
Stay on top of industry trends and best practices to continuously improve what we do and ensure our customer experience is the best it can be
Quickly learn the CarMax technology standards and norms and ensure that your teams follow best practices for change management, security, etc.
This role will have on‑call expectations to be available for major incidents and issues that affect your team’s applications.
Minimum Qualifications:
Bachelor’s Degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Optional for sponsorship needs: Master’s Degree in Computer Science, Computer Engineering, or relevant technical field
10+ years of software‑engineering experience in an enterprise‑level environment in one or more of the following areas: machine learning/artificial intelligence, cloud computing, systems engineering
5+ years’ experience managing direct reports
5+ years’ experience with microservices software architecture
5+ years leading the end‑to‑end design and development of scalable services to be consumed by the enterprise, including monitoring and production support
5+ years’ experience building enterprise‑level solutions with Microsoft Azure or equivalent cloud technologies
Demonstrated ability to provide vision for the Cloud Engineering, Software Engineering, and Machine‑Learning spaces and inspire teams towards the future
Proven ability to strategically prioritize by balancing business delivery and value generating work with technical debt and engineering excellence
Experience with scripting languages such as shell scripts
Experience in DevOps practices, testing frameworks, and CI/CD
Experience with Model Development and Deployment (MLFlow, Azure ML)
Experience with container orchestration (Kubernetes, Docker)
Experience communicating and working across functions to drive organization‑wide solutions
Preferred Qualifications:
Previous experience deploying large‑scale applications on Azure
Familiarity with MLOps and industry‑standard machine‑learning Python libraries
Experience with Azure AI services (Azure Machine Learning, Azure Cognitive Services)
Advanced AI/ML specializations (reinforcement learning, deep learning, NLP)
Proficient in an object‑oriented programming language (i.e. C#, Java)
Experience using large language models (LLMs) with semantic search frameworks for chatbot implementations
Software Specific Qualifications:
Experience building enterprise‑level solutions with Microsoft Azure or equivalent cloud technologies
Proficiency developing and debugging in Python
Experience with Model Development and Deployment (MLFlow, Azure ML)
Experience with Azure AI services (Azure Machine Learning, Azure Cognitive Services)
Experience with scripting languages such as shell scripts
Experience in DevOps practices, testing frameworks, and CI/CD
Experience with container orchestration (Kubernetes, Docker)
Richmond, VA
#J-18808-Ljbffr
Identify new opportunities for ML and AI solutions and build and cultivate relationships with leaders across the organization to foster those partnerships
Influence partners and stakeholders in Data Science and other teams across the organization to prioritize objectives and provide a comprehensive approach to solution recommendations that includes ROI, time to market, scalability as well as alternative recommendations
Communicate effectively with senior leadership to share progress, raise any roadblocks or impediments to delivery, and also spread awareness of your teams’ achievements
Create the strategic roadmap that will guide the direction and goals for the team, both in terms of individual project impacts but also overall standards for machine learning and AI utilization in the organization
Empower your direct reports to lead their teams by providing them with the resources, training, feedback, and a sounding‑board to be successful in their roles
Develop people through effective communication and ongoing feedback
Manage the budget of your area including budget planning and estimating costs of future development and tracking spend on an ongoing basis
Create an inclusive and engaging culture for a team of remote and hybrid engineers with varying levels of experience
Work through others to deliver resilient and scalable technology solutions that solve for complex business problems
Help drive the broader understanding of the use of machine learning and AI by interfacing with key roles in Operations, Legal, Security, and Technology
Stay on top of industry trends and best practices to continuously improve what we do and ensure our customer experience is the best it can be
Quickly learn the CarMax technology standards and norms and ensure that your teams follow best practices for change management, security, etc.
This role will have on‑call expectations to be available for major incidents and issues that affect your team’s applications.
Minimum Qualifications:
Bachelor’s Degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
Optional for sponsorship needs: Master’s Degree in Computer Science, Computer Engineering, or relevant technical field
10+ years of software‑engineering experience in an enterprise‑level environment in one or more of the following areas: machine learning/artificial intelligence, cloud computing, systems engineering
5+ years’ experience managing direct reports
5+ years’ experience with microservices software architecture
5+ years leading the end‑to‑end design and development of scalable services to be consumed by the enterprise, including monitoring and production support
5+ years’ experience building enterprise‑level solutions with Microsoft Azure or equivalent cloud technologies
Demonstrated ability to provide vision for the Cloud Engineering, Software Engineering, and Machine‑Learning spaces and inspire teams towards the future
Proven ability to strategically prioritize by balancing business delivery and value generating work with technical debt and engineering excellence
Experience with scripting languages such as shell scripts
Experience in DevOps practices, testing frameworks, and CI/CD
Experience with Model Development and Deployment (MLFlow, Azure ML)
Experience with container orchestration (Kubernetes, Docker)
Experience communicating and working across functions to drive organization‑wide solutions
Preferred Qualifications:
Previous experience deploying large‑scale applications on Azure
Familiarity with MLOps and industry‑standard machine‑learning Python libraries
Experience with Azure AI services (Azure Machine Learning, Azure Cognitive Services)
Advanced AI/ML specializations (reinforcement learning, deep learning, NLP)
Proficient in an object‑oriented programming language (i.e. C#, Java)
Experience using large language models (LLMs) with semantic search frameworks for chatbot implementations
Software Specific Qualifications:
Experience building enterprise‑level solutions with Microsoft Azure or equivalent cloud technologies
Proficiency developing and debugging in Python
Experience with Model Development and Deployment (MLFlow, Azure ML)
Experience with Azure AI services (Azure Machine Learning, Azure Cognitive Services)
Experience with scripting languages such as shell scripts
Experience in DevOps practices, testing frameworks, and CI/CD
Experience with container orchestration (Kubernetes, Docker)
Richmond, VA
#J-18808-Ljbffr