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 Operations Engineer to help build and maintain our cutting-edge machine learning pipeline and the critical tools and infrastructure that support it. This role entails a particular focus on cloud-based pipeline infrastructure, CI/CD, deep neural network architectures, cloud-based model training, data management, and inference-time optimization. You will work on a variety of customer-focused projects throughout the product development life cycle, from initial proofs of concept through robust production-ready implementations. You'll work in a small group of machine learning scientists collaborating with the core side software group, and others in our cross-functional team.
The ideal candidate will have 2-4 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 architecture design, traditional computer vision, 3D graphics and simulation, robotics, and full-stack development.
Primary Responsibilities:
- Expand the capabilities of our machine learning model pipeline with new features around model training infrastructure, model lifecycle tracking, automated model evaluation, and data management.
- 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.
- 2 years of professional software development experience.
- Experience with training and deploying machine learning models using cloud-based resources.
- Experience with deep neural networks for computer vision applications preferred.
- Experience with AWS services such as EC2, S3, EKS, and SageMaker.
- Experience with Infrastructure as Code frameworks like TerraForm 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 full-stack software development 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.