Base Salary
$200k - $220k/yr
Responsibilities
- Lead the end-to-end delivery of complex, cross-functional ML initiatives from requirements gathering through release.
- Architect and build the AI/ML layer for the DFM AI + IQE integration with Teamcenter and Designcenter.
- Design real-time ML serving architecture, low-latency signal paths, model data contracts, MLOps, governance, and observability.
- Develop scalable cloud-based production systems, real-time endpoints, and MLOps infrastructure.
- Solve ambiguous cross-domain technical problems and deliver solutions aligned with business and technical objectives.
- Set engineering standards, identify opportunities, and develop multi-quarter technical roadmaps.
- Apply automated testing, distributed computing, and secure software development practices.
- Collaborate with engineers, product managers, data scientists, and business stakeholders.
- Mentor engineers through design reviews, code reviews, and technical guidance.
- Evaluate and introduce relevant advances, tools, and frameworks in ML and AI.
Requirements
- Bachelor’s degree in a STEM field or equivalent experience.
- 6–8 years of machine learning engineering experience delivering complex ML systems in production.
- Deep expertise in machine learning and AI technologies, including gradient boosting, deep learning, and/or generative AI frameworks.
- Experience deploying real-time ML products at scale in cloud environments, including auto-scaling, monitoring, and alerting; AWS is strongly preferred.
- Strong Python proficiency and advanced ML/AI framework experience with TensorFlow, PyTorch, or similar.
- Strong software engineering fundamentals, including data structures and algorithms.
- Experience with MLOps practices such as model monitoring, drift detection, automated retraining, and redeployment pipelines.
- Proficiency with CI/CD pipelines, test-driven development, and infrastructure as code such as Terraform.
- Experience optimizing ML deployments for latency and throughput.
- Experience with transformers, self-supervised pre-training, large language models, or generative AI.
- Knowledge of containers, Kubernetes, and cloud-native distributed systems.
- Manufacturing, supply chain, or marketplace experience is preferred.
Benefits
- 401(k) match
- Medical, dental, and vision insurance
- Life and disability insurance
- Paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave
- Employee assistance program and other wellbeing resources
- Hybrid work arrangement
Tech Stack
Categories
About Xometry
Xometry is the digital engine behind the modern manufacturing revolution. By blending our AI-native platform with a massive global marketplace, we seamlessly connect enterprise buyers, from agile startups to Fortune 500 leaders, with a vetted network of expert suppliers. Whether you are building for the aerospace, defense, medical, automotive, or other industries, our platform helps you move from a digital concept to physical production with unmatched speed, predictability, and global scale. At our core, we power both sides of the manufacturing lifecycle. We streamline design and sourcing for engineers and procurement teams, while simultaneously giving independent machine shops the digital infrastructure they need to grow their business and book their idle capacity. Founded in 2013 and publicly traded since June 2021, Xometry has built a six-year streak on the Deloitte Technology Fast 500™, highlighting our rapid momentum as we redefine the economics of how things are made. www.xometry.com | info@xometry.com | 240.252.1138