Machine Learning Engineer North Bethesda, MD
Listed on 2026-06-06
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML 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. 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.
OverviewWe 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 will work closely with data scientists, engineers, and product managers to bring high‑impact ML capabilities into production.
Everything you build will matter.
- Lead with technical depth – Own the end‑to‑end lifecycle from requirements gathering through release, ensuring high‑quality, on‑time delivery across complex, cross‑functional initiatives.
- Own the partner integration AI/ML plane – Architect and build the high‑performance AI/ML layer of Xometry's embedded DFM AI + IQE integration with Teamcenter and Design center. Design the real‑time ML serving architecture and low‑latency signal path that delivers DFM and pricing feedback directly into the designer's environment, defining data contracts and implementing MLOps, governance, and observability.
- Build for scale – Develop cloud‑based production systems powering real‑time endpoints and MLOps, integrated with Xometry's broader systems and infrastructure.
- Solve ambiguous problems – Navigate complex, cross‑domain technical challenges, evaluate variable factors, and deliver solutions that meet both business and technical objectives.
- Set the standard – Proactively surface opportunity areas, take ownership of new processes and solutions, and develop multi‑quarter roadmaps.
- Champion quality and security – Apply best practices in automated testing, parallel and distributed computing, and secure software development across ML systems.
- Collaborate broadly – Partner with engineers, product managers, data scientists, and business stakeholders to translate requirements into robust technical solutions.
- Mentor and elevate – Guide other engineers through reviews and technical mentorship, raising overall team capability.
- Stay current – Keep pace with advances in ML/AI and bring relevant new approaches, tools, and frameworks into practice.
- Bachelor's degree in a STEM field (or equivalent) plus 6‑8 years of experience in machine learning engineering, owning and delivering complex ML systems in production.
- Deep expertise in ML and AI technologies:
Gradient Boosting, Deep Learning, and/or Generative AI frameworks, focusing on backend scalability and reusability. - Hands‑on experience deploying real‑time ML products at scale in cloud environments (AWS preferred), including auto‑scaling, monitoring, and alerting.
- Strong proficiency in Python and advanced ML/AI frameworks such as Tensor Flow or PyTorch.
- Solid grounding in software engineering fundamentals, data structures, and algorithms.
- Demonstrated experience with MLOps practices: model monitoring, data and concept drift detection, automated retraining and redeployment pipelines.
- Proficiency with CI/CD pipelines (e.g., Git Hub 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 work 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 such as 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.
Estimated base salary: $200,000‑$220,000 annually + commission. Benefits include 401(k) match, medical, dental, vision, life and disability insurance, paid time off, maternity and bonding leave, EAP, and other wellbeing resources.
Work Arrangement#LI-Hybrid
Equal Opportunity EmployerXometry 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 will provide required Form I‑9 information.
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