MLOps Engineer with Computer Vision Expertise - Remote

Overview

Fusemachines is a 10+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries. Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities. With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide. At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.

In Short

• Design, build, and maintain robust, scalable, and automated MLOps pipelines for model training, evaluation, and deployment (CI/CD for ML).
• Containerize machine learning applications using Docker for scalable and reproducible deployments.
• Deploy and manage ML models at scale.
• Optimize deep learning models for inference performance, including techniques like quantization, pruning, and distillation.
• Work with and extend state-of-the-art AI models for tasks such as depth estimation and object pose estimation.
• Develop and maintain monitoring systems to track model performance and ensure reliability of production systems.
• Collaborate with AI researchers and software engineers to transition models from research to production.
• Manage and optimize pipelines for processing large-scale 3D data.
• Apply strong mathematical understanding of spatial transformations and algorithmic integrity.

Requirements

• Bachelor's in Computer Science, Engineering, or a related field.
• Proven experience in an MLOps, DevOps, or similar role with a focus on machine learning.
• Strong programming skills in Python and/or C++.
• A portfolio of projects or publications in the field of computer vision or MLOps.
• Hands-on experience with model optimization techniques and frameworks.
• Hands-on experience with containerization technologies.
• Experience with CI/CD tools and version control.
• Solid understanding of general computer vision and 3D computer vision principles.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.
• A strong mathematical foundation in spatial transformations and triangulation.

Benefits

• Equal Opportunities Employer, committed to diversity and inclusion.