Principal ML Engineer, ML Platform Engineering

Xometry

North Bethesda (MD)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Join a forward-thinking company as a Principal Machine Learning Engineer, where you will lead innovative projects that power a digital marketplace. This high-visibility role offers the chance to work hands-on with cutting-edge technologies, mentor engineers, and shape the future of AI/ML solutions. You will have ownership of your work and the opportunity to drive significant impact within the organization, all while collaborating with a diverse team of experts. If you're passionate about machine learning and looking to challenge yourself in a dynamic environment, this is the perfect opportunity for you.

Qualifications

  • 7+ years of experience in machine learning or software engineering.
  • Experience designing cloud infrastructure for ML models.
  • Strong technical expertise in ML techniques and algorithms.

Responsibilities

  • Lead technical efforts by coding, troubleshooting, and mentoring.
  • Ensure operational excellence in ML infrastructure delivery.
  • Collaborate with product managers and data scientists.

Skills

Machine Learning Engineering
Software Engineering
Cloud Infrastructure (AWS)
Deep Learning (PyTorch, Tensorflow)
Infrastructure as Code (Terraform)
REST API Design
Python Programming
Multimodal Data Processing

Education

Bachelor's Degree in Computer Science
Master's Degree or PhD in related field

Tools

Docker
Kubernetes
AWS Services (SageMaker, Lambda, etc.)

Job description

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.


Responsibilities:



  • 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.


Qualifications:



  • 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. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following:


    • 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


      • Including large-scale language and vision models (Transformers, GPT, VLMs, LLMs), deep learning (PyTorch, Tensorflow)


    • 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, from executives to product managers and a wide variety of stakeholders and contributors

  • Experience in the manufacturing, supply chain, or similar industries is a plus.

  • Must be a US Citizen or Green Card holder (ITAR)


#LI-Hybrid

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.


For US based roles: 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.

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