Senior Manager, Machine Learning Engineering

We are seeking a highly skilled Machine Learning Engineering Manager with a strong background in ML Ops, infrastructure, and software engineering.

The ideal candidate will have at least 8+ years of total experience in the industry, including a minimum of 3 years in a leadership role.

This position requires both leadership and hands-on technical expertise, managing a team of engineers while actively contributing to the design, development, and deployment of machine learning models and systems. Key Responsibilities :

• Lead, mentor, and manage a team of machine learning engineers, providing guidance on best practices in ML Ops, infrastructure, and software engineering.
• Lead development of infrastructure for ML model training, testing, and deployment.
• 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, 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.

Qualifications :

• 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 leadership or 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.

Preferred Qualifications :

• 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).

LI-Hybrid

Here at Xometry we believe in diversity, equity, inclusion and belonging. We are committed to welcoming, respecting, and valuing people for who they are as individuals, learning from their differences, embracing their uniqueness, and providing a positive workplace for all.

Xometry is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.

Xometry participates in E-Verify and after a job offer is accepted, will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.