Staff Machine Learning Engineer

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. Xometrys 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 Staff Machine Learning Engineer to join our growing AI/ML team. This is asenior individual contributor role with broad technical scope and meaningful organizationalimpact. You will lead the design and delivery of complex ML systems architect integrationsacross our tech stack and set the engineering standard for how we build and deploy machinelearning solutions at scale. You will work closely with data scientists engineers and product managers to bring high-impact ML capabilities into production. Everything you build will matter.A defining piece of this role is owning the AI/ML architecture behind one of Xometrys highest-leverage strategic initiatives: the DFM AI IQE integration. You will be the data engineeringlead for the digital thread that connects Xometrys platform to our partners ecosystem Solid Edge NX Designcenter and Teamcenter building the pipelines contracts andobservability that move quotes parts manufacturability signals and pricing between the twosystems in real time. The system you design is what takes the innovative digital threadoperating at science fiction speed from ideation to reality.

Responsibilities

Qualifications

• Bachelors degree in a STEM field (or equivalent experience) plus 6-8 years of experience in machine learning engineering with a track record of owning and delivering complex ML systems in production.
• Deep expertise in ML and AI technologies including Gradient Boosting methods Deep Learning and/or Generative AI frameworks with a focus on backend scalability and
  reusability.
• Hands-on experience deploying real-time ML products at scale in cloud environments (AWS strongly preferred) including auto-scaling monitoring and alerting.
• Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow PyTorch or similar.
• Solid grounding in software engineering fundamentals data structures and algorithms.
• Demonstrated experience with MLOps practices: model monitoring data and concept drift detection and automated retraining and redeployment pipelines.
• Proficiency with CI/CD pipelines (e.g. Github actions)test driven development and infrastructure as code (e.g. Terraform).
• Experience profiling and optimizing existing ML model deployments for latency and throughput.
• Ability to operate independently on new and ambiguous assignments determine methods and procedures and communicate effectively across engineering product and
  business audiences.
• Experience with state-of-the-art modeling techniques including transformers self-supervised pre-training large language models (LLMs) or generative AI.
• Knowledge of containers container orchestration (Kubernetes) and cloud-native distributed systems.
• Background in manufacturing supply chain or marketplace environments is a plus but curiosity and drive matter more.

The estimated base salary range for new hires into this role is $200000-$220000.00 annually commission depending on factors such as job-related skills relevant experience and location. We also offer a competitive benefits package including 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; and much more.

#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.