Lead Machine Learning Engineer

Domino's Corporate•Ann Arbor, MI

7d•Onsite

About The Position

Leads the design, development, and deployment of machine learning models to address moderately complex to complex business challenges. Applies advanced technical expertise and organizational knowledge to independently solve problems that may lack well-defined solutions, ensuring alignment with strategic objectives and operational requirements.

Requirements

5 to 8 years of professional experience in machine learning engineering or related fields demonstrating mastery of advanced technical skills and independent project leadership.
Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline; advanced degrees preferred.
Advanced proficiency in machine learning algorithms, model development, and evaluation techniques.
Strong programming skills in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn.
Ability to independently solve complex problems with limited guidance, leveraging deep organizational and functional knowledge.
Effective communication skills, with the ability to articulate technical concepts and collaborate across teams.
Experience designing scalable machine learning systems and integrating them into production workflows.
Microsoft Azure (Azure Container Apps, Azure AI Services, Azure Storage, Azure Key Vault, Azure Monitor, Event Hubs, and related cloud services)
Azure Machine Learning for model development, deployment, monitoring, and lifecycle management
Databricks for data engineering, machine learning, and large-scale analytics
GitHub (GitHub Enterprise, Actions, and repository management) for source control, CI/CD, and DevOps automation
Python and associated ML libraries (TensorFlow, PyTorch, scikit-learn, Pandas, NumPy)
Containerization and orchestration technologies (Docker, Kubernetes, Azure Container Apps)
REST APIs and integration frameworks for connecting AI services, enterprise applications, and data platforms

Responsibilities

Serve as a senior technical resource for Machine Learning, AI, and Generative AI initiatives.
Provide technical leadership and mentorship to engineers and data scientists.
Translate business requirements into scalable, maintainable technical solutions.
Promote engineering best practices across software development, MLOps, and cloud-native platforms.
Collaborate with cross-functional teams to deliver business value through AI and data-driven solutions.
Contribute to the design and evolution of scalable ML/AI architectures and operational processes.
Evaluate emerging technologies and recommend opportunities for adoption when appropriate.
Conduct code reviews, design discussions, and technical troubleshooting sessions.
Design, develop, deploy, and support production ML and AI solutions using Azure, Databricks, and containerized services.
Build reusable frameworks, APIs, deployment patterns, and automation capabilities.
Partner with architects, engineers, and platform teams to deliver secure, scalable, and maintainable solutions.
Develop and operationalize machine learning and Generative AI solutions that support business objectives.
Integrate AI services, APIs, and enterprise data sources into production applications and workflows.
Contribute to model deployment, monitoring, and lifecycle management activities.
Participate in Agile ceremonies, technical planning, and solution design reviews.
Contribute to shared code repositories through peer reviews, testing, and continuous integration practices.
Support production deployments, incident response, troubleshooting, and root cause analysis efforts.