Manager - Machine Learning & Artificial Intelligence

Essential Functions:Translates the Company’s enterprise strategy into an actionable AI/ML roadmap focused on dental manufacturing, digital workflows, customer experience, knowledge access, marketing, operational automation, forecasting, and decision support. Develops business cases, success measures, and value-realization plans that link AI activity to outcomes such as time saved, quality improved, throughput increased, service consistency, revenue enabled, risk reduced, or cost avoided. Balances rapid experimentation with disciplined product management, production readiness, and long-term maintainability. Owns all phases of AI/ML development lifecycle from understanding business requirements, design and modeling, development, deployment, and support. Manages and executes project plans and delivery commitments, overseeing day-to-day activities of the engineering team within an Agile/Scrum environment. Collaborates with stakeholders and management to translate product visions, business cases and user experiences into technical requirements, scopes development efforts and assigns resources to execute against prioritized product roadmaps. Leads the machine learning and software engineering team in solving complex business problems using AI/Machine Learning and real-time dashboards. Defines and leads technology strategies, team direction, resolves problems and provides guidance to the team. Drives efficiencies and best practices across teams, keeping abreast of new technology and trends, making recommendations, and implementing improvements/upgrades as necessary. Designs, trains, and refines AI models to meet specific business needs or objectives, integrating AI capabilities with existing business systems to enhance efficiency and outcomes. Ensures the quality, accessibility, and security of data used for AI training and operations. Seamlessly integrates AI capabilities with existing business systems and workflows to enhance efficiency and outcomes. Navigates ethical considerations and ensures all AI solutions comply with legal and regulatory standards. Stays updated on the latest AI developments and technologies, exploring innovative approaches to apply AI within the enterprise. Establishes frameworks for the responsible use of AI, including performance monitoring, training documentation, bias mitigation, and security protocols. Vets and certifies AI-enabled services that the company will use, considering factors such as privacy, intellectual property, and accuracy, including coding assistants, ChatGPT/LLM tools, CX tools and models, cybersecurity tools, and finance tools. Creates a collaborative, psychologically safe environment where team members can challenge assumptions, learn from experiments, raise risks early, and share accountability for outcomes. Communicates priorities, tradeoffs, risks, and progress in plain language for executives, clinicians, laboratory leaders, operations teams, and technical staff. Builds trust through transparency, follow-through, empathy, sound judgment, and consistent communication. Participates and leads change management and AI adoption activities, including demonstrations, training, feedback loops, and practical guidance for users. Recognizes the operational expertise of laboratory and business teams and treat them as co-designers of AI solutions. Partners with internal team members to define and ensure data science best software engineering practices, providing technical mentorship in machine learning engineering and research topics including features engineering, analysis, modeling, and production development. Partners with Cybersecurity, Legal, Compliance, Privacy, Quality, and business leaders to establish practical AI governance that protects Glidewell information while enabling innovation. Ensures appropriate access control, data protection, audit logging, model and prompt versioning, source grounding, output review, incident response, and vendor assurance. Builds strong working relationships across laboratory operations, manufacturing, customer experience, marketing, finance, product, R&D, HR, Legal, Compliance, cybersecurity, and enterprise technology. Oversees assigned staff including but not limited to scheduling, directing, assigning work, and ensuring tasks/projects are completed in a timely manner and adheres to operational standards. Hires, trains, manages, develops, assigns, evaluates, and sets goals for department and staff. Serves as both coach and mentor to staff in areas of problem solving, decision making, process improvement, and professional growth in accordance with company policies. Coordinates with Human Resources and direct management in a timely manner on any and all employee relations matters. Conducts performance evaluations, recognizes, and acknowledges positive and productive behavior, and provides constructive/corrective feedback for performance issues. Performs other related duties and projects as business needs require at direction of management. Education and Experience:Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field required; advanced degree preferred. Minimum five (5) years of relevant working experience required. Understands fundamental concepts, practices and procedures of AI/ML field. Minimum five (5) years of experience in training, evaluating, optimizing, deploying, and maintaining AI/ML models on production systems required. Minimum five (5) years of experience in applying machine learning algorithms to solve a wide range of optimization problems like customer sales prediction, recommendation engine, sentiment analysis, deep learning with image and natural language, customer segmentations/clustering, object detection required. Minimum three (3) years of experience managing and leading a team of technical professionals including coaching, prioritization, hiring, and performance development. Prior experience with Python, SQL, APIs, cloud platforms, data pipelines, model serving, containerization, source control, CI/CD, and production monitoring. Prior experience with major AI/ML ecosystems such as PyTorch, TensorFlow, scikit-learn, Hugging Face, MLflow, Databricks, SageMaker, Bedrock, Azure AI, Azure OpenAI, Microsoft Fabric, or equivalent platforms. Pay Range: $152,000 to $200,000/yr