Xometry is seeking a skilled Senior Manager of Machine Learning Engineering to oversee ML Engineering efforts to productionize and deploy ML models that predict the cost to manufacture customers' parts and determine the best price to charge for them.
Requirements
- Strong understanding of machine learning frameworks, tools, and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with ML Ops practices, including model versioning, continuous integration, and automated deployment.
- Proficiency in software engineering practices, including object-oriented design, code versioning, and testing.
- Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and distributed computing.
- Experience with pricing algorithms
- Experience with neural networks and deep learning
- Experience with containerization technologies (e.g., Docker, Kubernetes).
Responsibilities
- Lead the productionization of ML models and their deployment to quickly iterate on ML at the core of our business
- Be hands-on in the design, development, and deployment of machine learning models and systems, ensuring they meet high standards of performance, scalability, and reliability.
- Develop and maintain ML Ops pipelines, ensuring efficient model training, deployment, and monitoring.
- Implement and manage infrastructure for large-scale data processing, model training, and inference.
- Drive continuous improvement in engineering practices, including code quality, testing, and deployment automation.
- Stay up-to-date with the latest trends and advancements in machine learning, software engineering, and cloud infrastructure to inform team strategy and direction.
- Lead, mentor, and manage a team of machine learning engineers, providing guidance on best practices in ML Ops, infrastructure, and software engineering.
Other
- 8+ years of experience in the industry, including a minimum of 3 years in a leadership role
- Must be a US Citizen or Green Card holder (ITAR)
- Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.
- Demonstrated ability to manage multiple projects simultaneously, prioritizing tasks and managing resources effectively.
- Manage project timelines, resources, and deliverables, ensuring projects are completed on time and within budget.
