Principal ML Engineer, ML Platform Engineering

Xometry-posted 10 months ago
Full-time • Senior
North Bethesda, MD
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Xometry (NASDAQ: XMTR) powers the industries of today and tomorrow by connecting the people with big ideas to the manufacturers who can bring them to life. Xometry’s digital marketplace gives manufacturers the critical resources they need to grow their business while also making it easy for buyers at Fortune 1000 companies to tap into global manufacturing capacity. We are looking for a principal machine learning engineer to join our core machine learning platform engineering team. In this role, you will partner closely with the AI/MLE leadership team to deliver the vision and technical implementation for the foundational infrastructure leveraged by Xometry’s AI/ML solutions, including the Instant Quoting Engine® and other AI/ML products powering the Xometry marketplace. This will be a high visibility role working hands-on to deliver a core aspect of the Xometry ecosystem. You will be given the opportunity to continually challenge yourself, drive innovation, have ownership of your work, and play a crucial role in the Xometry platform.

  • Adopt a 'lead by example' approach by actively coding and troubleshooting, as well as creating documentation and technical diagrams.
  • Serve as a mentor and guide to engineers across the organization, teaching and mentoring them to grow their skills.
  • Conduct code reviews and mentor others within the organization regarding best practices in ML Engineering.
  • Guarantee the delivery of superior infrastructure and software that meets and exceeds customer expectations, while aligning with strategic business timelines.
  • Forge strong partnerships with product managers, data scientists, and company leadership to promote a culture of open communication and integrated team dynamics.
  • Champion the adoption of cutting-edge technologies, methodologies, and practices to enhance problem-solving efficiency and effectiveness across the AI/ML organization.
  • At least 7 years of experience in machine learning engineering, software engineering, data science, or similar technical role.
  • A bachelor’s degree is required; an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is preferred and may substitute for some years of experience.
  • Demonstrated experience designing and deploying cloud infrastructure (AWS preferred) to support machine learning and machine learning models, with considerations for scale, reliability, and security.
  • Deep understanding of the machine learning lifecycle and related infrastructure needs - feature stores, a/b testing, model registration, drift detection, automated retraining, etc.
  • Strong technical expertise in software engineering principles, including parallel and distributed computing, version control, reproducibility, and continuous integration.
  • Ability to quickly build technical expertise in machine learning techniques and algorithms, with emphasis on their impact to infrastructure implementation.
  • Experience with large-scale language and vision models (Transformers, GPT, VLMs, LLMs), deep learning (PyTorch, Tensorflow).
  • Experience with Infrastructure as Code (IaC), especially Terraform.
  • Experience in REST API design and implementation.
  • Proficiency in object-oriented and functional programming in Python.
  • Experience with multimodal data processing (e.g., combining text, image, and 3D data).
  • Experience with AWS microservices including SageMaker, Service Catalog, IAM, Lambda, Cloudwatch, ECR, EKS, and Kinesis.
  • Experience with containerization technologies (Docker and Kubernetes).
  • Demonstrated ability to interact and communicate effectively at all levels of the organization, from executives to product managers and a wide variety of stakeholders and contributors.
  • Experience in the manufacturing, supply chain, or similar industries.
  • Diversity, equity, inclusion and belonging initiatives.
  • Equal opportunity employer.
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