Principal Ml Engineer
Xometry
Job highlights
Summary
Join Xometry's core machine learning platform engineering team as a Principal Machine Learning Engineer. Partner with AI/MLE leadership to build foundational infrastructure for AI/ML solutions like the Instant Quoting Engine. This high-visibility role involves hands-on development, mentorship, and collaboration with various teams. You'll champion innovation, guide best practices, and ensure superior infrastructure delivery. The position requires extensive experience in machine learning engineering and cloud infrastructure (AWS preferred). A strong technical background in software engineering principles, machine learning techniques, and various technologies is essential.
Requirements
- At least 7 years of experience in machine learning engineering, software engineering, data science, or similar technical role
- A bachelorβs degree is required, but an advanced degree (M.S. or PhD) in computer science, machine learning, AI, or a related field is preferred and may substitute for some years of experience
- Demonstrated experience designing and deploying cloud infrastructure (AWS preferred) to support machine learning, and machine learning models, with considerations for scale, reliability and security
- Deep understanding of the machine learning lifecycle and related infrastructure needs - feature stores, a/b testing, model registration, drift detection, automated retraining, etc
- Strong technical expertise. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following: Software engineering principles, including parallel and distributed computing, version control, reproducibility, and continuous integration
- Strong technical expertise. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following: Machine learning techniques and algorithms, with emphasis on their impact to infrastructure implementation Including large-scale language and vision models (Transformers, GPT, VLMs, LLMs), deep learning (PyTorch, Tensorflow)
- Strong technical expertise. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following: Infrastructure as Code (IaC), especially Terraform
- Strong technical expertise. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following: REST API design and implementation
- Strong technical expertise. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following: Object oriented and functional programming in Python
- Strong technical expertise. You will need to either have or demonstrate the ability ability to quickly build technical expertise in the following: Multimodal data processing (e.g., combining text, image, and 3D data)
- Experience with AWS microservices including SageMaker, Service Catalog, IAM, Lambda, Cloudwatch, ECR, EKS, and Kinesis
- Containerization technologies (Docker and Kubernetes)
- Demonstrated ability to interact and communicate effectively at all levels of the organization, from executives to product managers and a wide variety of stakeholders and contributors
- Must be a US Citizen or Green Card holder (ITAR)
Responsibilities
- Adopt a 'lead by example' approach by actively coding and troubleshooting, as well as creating documentation and technical diagrams
- Serve as a mentor and guide to engineers across the organization, teaching and mentoring them to grow their skills
- Do code review and mentor others within the organization regarding best practices in ML Engineering
- Guarantee the delivery of superior infrastructure and software that not only meets but exceeds customer expectations, while aligning with the strategic business timelines
- Forge strong partnerships with product managers, data scientists, and company leadership to promote a culture of open communication and integrated team dynamics
- Champion the adoption of cutting-edge technologies, methodologies, and practices to enhance problem-solving efficiency and effectiveness across the AI/ML organization
Preferred Qualifications
Experience in the manufacturing, supply chain, or similar industries is a plus
Benefits
#LI-Remote
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