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.
Xometry is looking for a Principal Machine Learning Engineer to join our growing organization. The right person will help move our machine learning capabilities to the next level. You’ll be working in an organization where AI is the enabler and center of its core business strategy. You want to be part of a small, intensely skilled team, who feel total ownership of their work, and can’t imagine a day without learning & coding. You will play a crucial role in the Xometry platform and everything you do will matter.
What You’ll Do
- At Xometry, you will play a crucial role in exploring new machine learning opportunities, researching and performing proof of concepts, and bringing new machine learning and AI solutions into Xometry’s platform
- Develop and implement machine learning models that improve Xometry’s ability to predict cost, price, and sourcing options for our customers and suppliers.
- You will be responsible for leading the evaluation of emerging technologies, identifying areas for improvement, and developing new features while ensuring the reliability and scalability of Xometry’s platform
- Lead the exploration of emerging AI and machine learning technologies and develop proof-of-concepts to assess their potential impact on Xometry’s platform
- Collaborate with cross-functional teams to gather requirements, prioritize features, and define technical solutions based on the latest innovations
- Monitor machine learning models and AI performance and troubleshoot issues as they arise
- Contribute to the documentation and knowledge base to help other teams understand and use Xometry’s AI effectively
What We’re Looking For
- Experience with state of the art ML modeling techniques and approaches like transformers, self supervised pre-training, generative modeling, LLMs, etc
- Experience with large scale data processing (e.g., Hands-on experience training and applying models at scale using deep learning frameworks like PyTorch or Tensorflow)
- Successful candidates in this role need to be able to bridge state of the art approaches to real world impact
- A cloud-native software craftsperson with hands on experience with containers, container orchestration, and distributed systems
- An engineer with a self-driven attitude who can own problems and deliver solutions
- Strong software fundamentals with experience in design patterns, refactoring, OOP, and testing
- A cloud practitioner who values the “shift-left” mentality by building systems with Infrastructure as Code, not console clicking
- Data’s at the heart of our systems, we hope it's yours too. You’re comfortable working with SQL and/or NoSQL, understand database design, and data analysis
- Experience building and consuming CI/CD pipelines
- Someone who knows their way around the command line and has experience working with *nix systems
- 8+ years working experience in the engineering teams that build large-scale ML-driven user-facing products
- 3+ years experience leading cross-team engineering efforts
- Strong execution skills in project management
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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.