We are looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact. You will lead the design and delivery of complex ML systems, architect integrations across our tech stack, and set the engineering standard for how we build and deploy machine learning 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 Xometry's highest-leverage strategic initiatives: the DFM AI + IQE integration. You will be the data engineering lead for the digital thread that connects Xometry's platform to our partner’s ecosystem — Solid Edge, NX, Designcenter, and Teamcenter — building the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between the two systems in real time. The system you design is what takes the innovative digital thread operating at "science fiction speed" from ideation to reality.

Responsibilities

Qualifications

• Bachelor's 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 $200,000-$220,000.00 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.

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