Sr Manager AI ML

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 Car Max 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.

• 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 toward 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 Dev Ops 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

• 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

• 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 Dev Ops practices, testing frameworks, and CI/CD
• Experience with container orchestration (Kubernetes, Docker)

Mid‑Senior level

Full‑time

Retail

• Medical insurance
• Vision insurance
• 401(k)
• Paid paternity leave
• Paid maternity leave
• Tuition assistance
• Student loan assistance
• Disability insurance