Senior ML Engineer - Real-Time AI Platform

Xometry; Denver (CO); Hybrid; USD 200,000 - 220,000; Full time

Benefits offered by this job

401(k) match

Medical, dental and vision

Life and disability insurance

Generous paid time off

Job summary

Xometry, a NASDAQ: XMTR company, is seeking a Staff Machine Learning Engineer to lead end-to-end ML systems design and delivery. You will own the AI/ML architecture behind the DFM AI + IQE integration, and build real-time ML serving pipelines within a cloud-scale, secure environment.

You'll collaborate with data scientists, engineers, and product managers to deploy high-impact capabilities, set engineering standards, and mentor team members while staying current with advances in ML/AI.

Qualifications

• Bachelor's degree in a STEM field plus 6–8 years of experience in machine learning engineering.
• Deep expertise in ML/AI technologies including Gradient Boosting, Deep Learning, and Generative AI with focus on backend scalability.
• Experience deploying real-time ML products at scale in cloud environments (AWS preferred).

Responsibilities

• Lead end-to-end lifecycle from requirements gathering through release for complex, cross-functional initiatives.
• Architect and build high-performance AI/ML layer for the DFM AI + IQE integration with Teamcenter and Designcenter.
• Develop cloud-based production systems powering real-time endpoints and MLOps.
• Navigate complex technical challenges and deliver solutions aligning business and technical objectives.
• Mentor engineers through design and code reviews and elevate team capability.
• Stay current with advances in ML/AI and bring new approaches into practice.

Skills

Python

TensorFlow

PyTorch

MLOps

CI/CD

Kubernetes

AWS

ML model deployment

Education

Bachelor's degree in STEM

Tools

Terraform

GitHub Actions

Job description

Xometry, a NASDAQ: XMTR company, is seeking a Staff Machine Learning Engineer to lead end-to-end ML systems design and delivery. You will own the AI/ML architecture behind the DFM AI + IQE integration, and build real-time ML serving pipelines within a cloud-scale, secure environment.

You'll collaborate with data scientists, engineers, and product managers to deploy high-impact capabilities, set engineering standards, and mentor team members while staying current with advances in ML/AI.