About this role
The AI and machine learning team at Xometry powers a digital marketplace that connects buyers at Fortune 1000 companies with global manufacturing capacity. This senior individual contributor role centers on building the AI and machine learning architecture behind the DFM AI and IQE integration, connecting the platform to partner ecosystems such as Solid Edge, NX, Designcenter, and Teamcenter.
Day-to-day work involves leading the design and delivery of complex machine learning systems, architecting real-time serving infrastructure, and establishing engineering standards for production deployments. The engineer in this position will create the data pipelines, contracts, and observability required to move quotes, parts, and pricing signals in real time.
An ideal candidate possesses deep technical expertise in machine learning engineering, a background in deploying cloud-based production systems, and the ability to solve ambiguous technical problems independently. Someone who thrives in cross-functional environments and enjoys mentoring peers will do well here.
What you will do
- Lead the end-to-end lifecycle of complex machine learning initiatives from requirements gathering to release.
- Architect and build the high-performance AI and machine learning layer for the embedded DFM AI and IQE integration.
- Design real-time ML serving architectures and low-latency signal paths to deliver feedback directly into designer environments.
- Develop cloud-based production systems that power real-time endpoints and integrate with broader company infrastructure.
- Apply automated testing, distributed computing, and secure software development practices across machine learning systems.
- Collaborate with data scientists, product managers, and engineers to translate business requirements into technical solutions.
- Mentor other engineers through design reviews, code reviews, and technical guidance.
What you need
- Bachelor degree in a STEM field or equivalent practical experience.
- Six to eight years of experience in machine learning engineering with a history of delivering complex production systems.
- Deep expertise in machine learning and artificial intelligence technologies including Gradient Boosting, Deep Learning, or Generative AI.
- Hands-on experience deploying real-time ML products at scale in cloud environments, with AWS strongly preferred.
- Strong proficiency in Python alongside advanced frameworks such as TensorFlow or PyTorch.
- Demonstrated experience with MLOps practices including model monitoring, drift detection, and automated retraining pipelines.
- Proficiency with CI/CD pipelines, test-driven development, and infrastructure as code tools like Terraform.
Nice to have
- Background in manufacturing, supply chain, or marketplace environments
- Experience with state-of-the-art modeling techniques like transformers and large language models
- Knowledge of containers, Kubernetes, and cloud-native distributed systems
Benefits
- 401(k) match
- Medical, dental, and vision insurance
- Life and disability insurance
- Generous paid time off including vacation, sick leave, and holidays
- Maternity and bonding leave
- Employee assistance program and wellbeing resources
Skills and tech stack
Questions candidates ask
What is the location and work policy for this role?
This is a full-time role based in Denver, CO, with a hybrid work structure.
What is the salary range for this position?
The estimated base salary range for new hires is $200,000 to $220,000 annually, plus a bonus depending on skills, relevant experience, and location.
What primary project will this engineer own?
A defining piece of this role is owning the AI and machine learning architecture behind the DFM AI plus IQE integration with Teamcenter and Designcenter.
What cloud environment does the team prefer?
Hands-on experience deploying real-time machine learning products at scale in cloud environments is required, with AWS strongly preferred.