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Xometry

Where Big Ideas Are Built

Principal ML Engineer, ML Platform Engineering

Platform EngineerPlatform EngineerFull TimeRemoteLeadTeam 1,001-5,000Since 2013H1B SponsorCompany SiteLinkedIn

Location

Maryland

Posted

119 days ago

Salary

$140K - $182K / year

Seniority

Lead

Job Description

Principal ML Engineer, ML Platform Engineering

Xometry

• Hands-On Technical Leadership: Adopt a 'lead by example' approach by actively coding and troubleshooting, as well as creating documentation and technical diagrams. • Teaching & Mentorship: You will serve as a mentor and guide to engineers across the organization, teaching and mentoring them to grow their skills. • Code Review: You will do code review and mentor others within the organization regarding best practices in ML Engineering. • Operational Excellence: Guarantee the delivery of superior infrastructure and software that not only meets but exceeds customer expectations, while aligning with the strategic business timelines. • Collaborative Strategy: Forge strong partnerships with product managers, data scientists, and company leadership to promote a culture of open communication and integrated team dynamics. • Guide Innovation: Champion the adoption of cutting-edge technologies, methodologies, and practices to enhance problem-solving efficiency and effectiveness across the AI/ML organization.

Job Requirements

  • At least 7 years of experience in machine learning engineering, software engineering, data science, or similar technical role.
  • A bachelor’s degree is required, but 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.
  • Software engineering principles, including parallel and distributed computing, version control, reproducibility, and continuous integration.
  • Machine learning techniques and algorithms, with emphasis on their impact to infrastructure implementation.
  • Infrastructure as Code (IaC), especially Terraform.
  • REST API design and implementation.
  • Object oriented and functional programming in Python.
  • 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.
  • Containerization technologies (Docker and Kubernetes).
  • Demonstrated ability to interact and communicate effectively at all levels of the organization...

Benefits

  • 401(k) match
  • medical, dental and vision insurance
  • life and disability insurance
  • generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave
  • EAP, other wellbeing resources

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