Machine Learning Platform Engineer

Oxipital AI is on a mission to revolutionize the manufacturing industry with its cutting-edge AI-enabled machine vision solutions. These solutions drive greater resilience, operational efficiency, and sustainability in the most complex and critical manufacturing processes. As a fast-growing company striving to make a difference every day, we are seeking a Machine Learning Platform Engineer to help build and maintain our V-CORTX platform and the critical tools and infrastructure that support it. This role entails a particular focus on AWS architecture, containerized CI/CD workflows, full-stack software engineering, deep neural network optimization, cloud-based model training, and data management. You'll work in a small group of machine learning scientists, collaborating with the cloud engineering team and others in our cross-functional organization.

The ideal candidate will have 3-5 years of professional experience designing and implementing high-performance software products in a production environment, and is comfortable working in a fast-paced dynamic environment. We are looking for hands-on work experience in several of the following areas: ML model training using AWS resources, CI/CD pipelines for machine learning, vision-based deep learning, edge deployment, neural network optimization, and full-stack development.

Primary Responsibilities:

Expand the capabilities of our V-CORTX cloud platform with new features around model training infrastructure, evaluation, deployment, managing isolated real and synthetic multi-tenant data, and annotation. Use best practices to minimize the cost footprint of model development. Optimize the efficiency of our machine learning models at training and inference time. Design, develop, and maintain tools and infrastructure for training, deploying, and evaluating vision-based machine learning models. Contribute to a robust and scalable product pipeline.

Requirements:

Bachelors degree or equivalent experience in Computer Science, Computer Engineering, or related technical field; graduate degree preferred. 3-5 years of professional software development experience. Experience with AWS services such as EC2, S3, ECS, and Batch. And database services like DynamoDB. Experience with training and deploying machine learning models using cloud-based resources. Experience with full-stack development, especially serverless architecture on AWS Experience with Infrastructure as Code frameworks, CloudFormation preferred. Strong proficiency in Python, particularly with libraries like PyTorch, NumPy, or OpenCV. Experience with software development and deployment in a Linux environment. A solid foundation of software development best practices such as issue tracking, static code checking, and automated testing preferred. Experience with deep neural networks for computer vision applications preferred. Strong mathematical and analytical skills. Excellent written and verbal communication skills. Ability to work both independently and collaboratively on a cross-functional team. Strong attention to detail.