Cloud ML Platform Engineer – Vision AI on AWS

Oxipital AI, Inc.; Bedford (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

Oxipital AI, Inc. is seeking a Machine Learning Platform Engineer to design and maintain the V-CORTX platform and its critical tooling.

You will focus on AWS-based architecture, containerized CI/CD workflows, full-stack engineering, and neural network optimization for production-grade computer vision solutions. The ideal candidate has 3–5 years of experience building high-performance software in production, with hands-on ML model training on AWS, edge deployment, and experience with serverless

Qualifications

• Bachelor's degree or equivalent in CS/EE or related field.
• 3–5 years of professional software development experience.
• Experience with AWS services (EC2, S3, ECS, Batch) and DynamoDB.
• Experience with training and deploying ML models using cloud resources.
• Experience with full-stack development, especially serverless on AWS.
• Infra as Code frameworks; CloudFormation preferred.

Responsibilities

• Expand V-CORTX cloud platform with model training, evaluation, deployment features.
• Minimize cost footprint of model development.
• Optimize ML models during training and inference.
• Build tools and infrastructure for training, deploying, and evaluating vision-based ML models.
• Contribute to a robust, scalable product pipeline.

Skills

Python

PyTorch

NumPy

OpenCV

Linux

AWS

CI/CD

Serverless

Education

Bachelor's degree or equivalent

Graduate degree preferred

Tools

CloudFormation

Job description

Oxipital AI, Inc. is seeking a Machine Learning Platform Engineer to design and maintain the V-CORTX platform and its critical tooling.

You will focus on AWS-based architecture, containerized CI/CD workflows, full-stack engineering, and neural network optimization for production-grade computer vision solutions. The ideal candidate has 3–5 years of experience building high-performance software in production, with hands-on ML model training on AWS, edge deployment, and experience with serverless