ML Platform Engineer: AWS Cloud, Vision, & CI/CD

oxipitalai; Bedford (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

Oxipital AI, based in Bedford, MA, is seeking a Machine Learning Platform Engineer to build and maintain the V-CORTX platform and its training, deployment, and data-management tools. This role emphasizes cloud resources, containerized CI/CD workflows, deep neural network optimization, and full-stack development within a fast-paced team.

The candidate will work with ML scientists and cloud engineers to design scalable infrastructure, optimize models, and manage multi-tenant data, while applying

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related technical field; graduate degree preferred.
• 3-5 years of professional software development experience.
• Experience with AWS services (EC2, S3, ECS, Batch) and DynamoDB.
• Experience with training and deploying machine learning models using cloud-based resources.

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.

Job description

Oxipital AI, based in Bedford, MA, is seeking a Machine Learning Platform Engineer to build and maintain the V-CORTX platform and its training, deployment, and data-management tools. This role emphasizes cloud resources, containerized CI/CD workflows, deep neural network optimization, and full-stack development within a fast-paced team.

The candidate will work with ML scientists and cloud engineers to design scalable infrastructure, optimize models, and manage multi-tenant data, while applying