Machine Learning Operations Engineer

Job DescriptionJob DescriptionSalary:

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. Youll 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 .
• 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 .
• Experience with AWS services such as EC2, S3, EKS, and SageMaker.
• Experience with Infrastructure as Code frameworks like TerraForm .
• 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 .
• Experience with full-stack software development .
• 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.

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