Description

As a Machine Learning Infrastructure Engineer, you will support the development of innovative ML technologies for Spectacles, collaborating with global teams to build scalable pipelines and optimize workflows for cutting-edge applications.

Requirements

• •Excellent software design, development and debugging skills
• •Proven track record of developing highly available systems
• •Working knowledge of ML fundamentals
• •Strong communications and interpersonal skills
• •Genuine passion for learning new things
• •Ability to travel as needed
• •Bachelors’ degree in a technical field or equivalent experience
• •2+ years of relevant industry experience
• •Experience with Python, C++ or equivalent
• •Experience with machine learning platforms and infrastructure
• •Experience building large scale production machine learning systems
• •Experience with Docker, Kubernetes, Istio/Envoy, NoSQL solutions
• •Experience with Tensorflow, PyTorch, or related deep learning frameworks
• •Experienced in MLOps: managing production machine learning lifecycle
• •Familiarity with Metaflow, Airflow, Kubeflow or similar workflow orchestration framework

Tasks

• •Own the ML platform for training, evaluation, and deployment of ML models
• •Build scalable data and training pipelines
• •Deliver scalable, reproducible end-to-end ML workflows
• •Develop optimization and release toolchain for automated testing and validation
• •Implement CI/CD for ML, quantization, distillation, and packaging
• •Advocate for best practices in scalability and cost management
• •Collaborate with cross-functional engineering and research teams

Tools & Technologies

Benefits