Machine Learning Platform Engineer

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 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 entitles 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:

• Bachelor's 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.