2 months ago
Responsibilities
- Lead the end-to-end lifecycle of complex ML systems from requirements gathering through production release.
- Architect and build the real-time AI/ML layer, data contracts, low-latency signal path, MLOps, governance, and observability for the DFM AI + IQE integration.
- Develop scalable cloud-based production systems, real-time endpoints, and distributed ML infrastructure.
- Profile and optimize ML deployments for latency and throughput while implementing monitoring, alerting, drift detection, and automated retraining and redeployment.
- Establish engineering standards, identify opportunities, and create multi-quarter technical roadmaps.
- Apply automated testing, parallel and distributed computing, and secure software development practices.
- Collaborate with engineering, product, data science, and business stakeholders to deliver robust technical solutions.
- Mentor engineers through design reviews, code reviews, and technical guidance.
Requirements
- Bachelor’s degree in a STEM field or equivalent experience.
- 6–8 years of experience in machine learning engineering with a record of delivering complex ML systems in production.
- Deep expertise in machine learning and AI technologies, including gradient boosting, deep learning, and/or generative AI frameworks.
- Hands-on experience deploying real-time ML products at scale in cloud environments, preferably AWS, including autoscaling, monitoring, and alerting.
- Strong proficiency in Python and advanced ML/AI frameworks such as TensorFlow or PyTorch.
- Strong software engineering fundamentals, including data structures and algorithms.
- Experience with MLOps, model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines.
- Experience with GitHub Actions or similar CI/CD pipelines, test-driven development, and infrastructure as code such as Terraform.
- 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
- Competitive benefits package including a 401(k) match.
- Medical, dental, and vision insurance, plus life and disability insurance.
- Generous paid time off including vacation, sick leave, floating and fixed holidays, maternity leave, and bonding leave.
- Employee assistance program and other wellbeing resources.
- Hybrid work arrangement, as indicated by the #LI-Hybrid designation.
Tech Stack
Categories
About Xometry
Xometry builds an AI-enabled marketplace that connects engineers and procurement teams with a vetted global network of manufacturers for on-demand CNC machining, 3D printing, sheet metal, and injection molding. The company earns fees by brokering instant-quote RFQs and managing production, logistics, and quality across its supplier base. Founded in 2013, Xometry is a publicly traded company (NASDAQ: XMTR) based in the Washington, DC–Baltimore area and serves buyers from startups to Fortune 1000 firms.