5 months ago
Base Salary
$200k - $220k/yr
Responsibilities
- Lead the end-to-end lifecycle of complex, cross-functional ML initiatives from requirements gathering through release.
- Architect and build the real-time AI/ML layer for the DFM AI + IQE integration with Teamcenter and Designcenter.
- Design ML serving architecture, low-latency signal paths, model input and output data contracts, MLOps, governance, and observability.
- Develop scalable cloud-based production systems, real-time endpoints, and MLOps infrastructure.
- Solve complex, ambiguous technical problems while balancing business and engineering objectives.
- Set technical standards, identify opportunities, and develop multi-quarter technical roadmaps.
- Apply automated testing, distributed computing, and secure software development practices across ML systems.
- Collaborate with engineers, product managers, data scientists, and business stakeholders to deliver robust solutions.
- Mentor engineers through design reviews, code reviews, and technical guidance.
- Evaluate and apply 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.
- Hands-on experience deploying real-time ML products at scale in cloud environments, with auto-scaling, monitoring, and alerting; AWS is strongly preferred.
- Strong Python proficiency and advanced ML/AI framework experience such as TensorFlow or PyTorch.
- Strong foundations in software engineering, data structures, and algorithms.
- Experience with MLOps practices including model monitoring, data and concept drift detection, and automated retraining and redeployment pipelines.
- Proficiency with CI/CD pipelines, test-driven development, and infrastructure as code such as Terraform.
- Experience profiling and 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 a plus.
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 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.