Principal ML Engineer – ML Platform Engineering
| Company | Xometry |
|---|---|
| Location | North Bethesda, MD, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s, PhD |
| Experience Level | Senior, Expert or higher |
Requirements
- At least 7 years of experience in machine learning engineering, software engineering, data science, or similar technical role.
- A bachelor’s 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 in software engineering principles, including parallel and distributed computing, version control, reproducibility, and continuous integration.
- Strong technical expertise in 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 in Infrastructure as Code (IaC), especially Terraform.
- Strong technical expertise in REST API design and implementation.
- Strong technical expertise in object oriented and functional programming in Python.
- Strong technical expertise in 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.
- Experience with 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.