• Degree in applied mathematics, statistics, computer science, physics, engineering, a quantitative or computation field. MS or PhD preferred
• 3+ years experience in building ML infrastructure in production environments
• Fluent in Python and writing production ready code
• Experience with Docker/Kubernetes
• Knowledgeable about cloud platforms such as GCP or AWS
• Experience using CI/CD platforms to automate build, test, and deployment pipelines
• Familiar with a variety of machine learning techniques and their real-world advantages/drawbacks

Desirable

• We are seeking a highly-skilled and experienced MLOps Engineer to join our team with demonstrable experience in designing and building scalable machine learning systems
• As a valued member of the team at CloudFactory, you will play a crucial role in developing and implementing cutting-edge software solutions that enhance our machine learning and core business capabilities
• You will work closely with cross-functional teams to design and build ML pipelines to support automation, reliability, and scalability of our computer vision models in a production setting
• If you are enthusiastic about the opportunity to make a difference in the world while working alongside talented individuals from developing nations, then CloudFactory is the perfect fit for you
• In this role, you would have a high degree of autonomy and be responsible for designing and implementing new core MLOps components, as well as optimizing or improving upon existing ML operations such as model training, inferencing, or high throughput batch jobs
• Further responsibilities would include developing CI/CD pipelines to automate model testing, deployment, and monitoring
• You would collaborate closely with ML engineers and be able to communicate complex issues clearly to stakeholders from the tech, product, or business teams