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Staff Machine Learning Engineer

Xometry Lexington, KY

Lexington, KY

Today

Full time Ai Ml Artificial Intelligence Cloud

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Job Description

Join Xometry’s AI/ML team in Lexington, KY (hybrid) as a Staff Machine Learning Engineer, leading end-to-end delivery of complex ML systems and partner integrations.

Responsibilities

Technical ownership across the lifecycle: lead requirements gathering through release, delivering high-quality results on time across complex, cross-functional initiatives
Partner integration AI/ML architecture: architect and build the high-performance AI/ML layer of the embedded DFM AI + IQE integration with Teamcenter and Designcenter
Real-time ML serving: design serving architecture and a low-latency signal path to deliver DFM and pricing feedback directly into the designer’s environment
Define ML data contracts: specify model input/output contracts and implement MLOps, governance, and observability for a mission-critical, public-marketplace partner integration
Cloud production systems: develop cloud-based systems for real-time endpoints and MLOps, integrated with Xometry’s broader systems and infrastructure
Cross-domain problem solving: evaluate variable factors and deliver solutions aligned with both business and technical objectives
Roadmapping and process improvement: identify opportunity areas, own new processes and solutions, and develop multi-quarter roadmaps for key technical objectives
Engineering quality and security: apply best practices in automated testing, parallel and distributed computing, and secure software development for ML systems
Collaborate across functions: work with engineers, product managers, data scientists, and business stakeholders to translate requirements into robust solutions
Mentorship and reviews: conduct design reviews, code reviews, and technical mentorship to raise team capability
Stay current: keep pace with ML/AI advances and bring relevant new approaches, tools, and frameworks into practice

Requirements

Bachelor’s degree in a STEM field (or equivalent experience) plus 6–8 years of machine learning engineering experience
Production ML ownership: proven track record owning and delivering complex ML systems in production
ML/AI expertise: deep knowledge of ML and AI technologies, including Gradient Boosting and Deep Learning and/or Generative AI frameworks, with a focus on backend scalability and reusability
Real-time ML at scale: hands-on experience deploying real-time ML products in cloud environments; AWS strongly preferred, including monitoring, alerting, and auto-scaling
Python and frameworks: strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow or PyTorch
Software engineering fundamentals: solid grounding in data structures and algorithms
MLOps experience: model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines
Delivery and infrastructure practices: CI/CD pipelines (e.g., GitHub Actions), test-driven development, and infrastructure as code (e.g., Terraform)
Performance optimization: experience profiling and optimizing ML deployments for latency and throughput
Independent execution: ability to operate on new and ambiguous assignments, determine methods and procedures, and communicate effectively across engineering, product, and business audiences
Modern modeling exposure: transformers, self-supervised pre-training, LLMs, or generative AI experience
Cloud-native systems: knowledge of containers, Kubernetes, and cloud-native distributed systems
Domain experience: manufacturing, supply chain, or marketplace background is a plus

Technologies

Python
TensorFlow
PyTorch
Gradient Boosting
Deep Learning
Generative AI frameworks
AWS
CI/CD pipelines
GitHub Actions
Test driven development
Terraform
MLOps
Model monitoring
Data and concept drift detection
Auto-scaling
Containers
Kubernetes
Transformers
Self-supervised pre-training
Large language models (LLMs)
Solid Edge
NX
Designcenter
Teamcenter
Parallel and distributed computing

Benefits

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 and other wellbeing resources

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