Senior Manager, ML Engineering

Summary

Join Xometry as a Senior Manager of Machine Learning Engineering and lead a team in productionizing and deploying ML models for pricing and cost prediction. This crucial role requires 8+ years of experience, including 3+ years in leadership, and expertise in ML model development and deployment. You will manage a team, collaborate with cross-functional stakeholders, and ensure high-performance, scalable, and reliable ML systems. The position demands strong technical skills, leadership abilities, and a commitment to continuous improvement. This is a remote position.

Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Engineering, or a related field
• 8+ years of experience in software engineering, with a focus on machine learning, ML Ops, and infrastructure
• Minimum of 3 years of experience in a management role, with a proven track record of leading engineering teams to successful project outcomes
• 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
• Strong problem-solving skills, with the ability to lead teams in troubleshooting complex technical challenges
• 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
• Must be a US Citizen or Green Card holder (ITAR)

Responsibilities

• Lead, mentor, and manage a team of machine learning engineers, providing guidance on best practices in ML Ops, infrastructure, and software engineering
• 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
• Collaborate with data scientists, product managers, software engineers, and other stakeholders to define project requirements and deliverables
• 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
• Manage project timelines, resources, and deliverables, ensuring projects are completed on time and within budget
• Foster a culture of innovation, collaboration, and continuous learning within the engineering team

Preferred Qualifications

• Experience with pricing algorithms
• Experience with neural networks and deep learning
• Experience with containerization technologies (e.g., Docker, Kubernetes)
• Knowledge of big data technologies (e.g., Hadoop, Spark) and data engineering practices
• Experience with CI/CD pipelines and automation tools (e.g., Jenkins, GitLab CI)

Benefits

Remote work