Machine Learning Ops Engineer

Must haves

• Good experience in OOP Python
• Good CI/CD experience. (Preferably Jenkins)
• IAC experience

• Has bachelor’s or master’s Degree in a technology related field (e.g. Computer Science, Engineering, etc.).

• Proven experience in building cloud-native applications using a range of AWS services, including but not limited to Sage Maker AI, Bedrock, S3, Cloud Formation (CFT), SNS, SQS, Lambda, AWS Batch, Step Functions, Event Bridge, and Cloud Watch. Familiarity with both Azure Cognitive Services, particularly for deploying OpenAI models, and Google Compute Vertex is beneficial.
• Strong experience with CI/CD tools, particularly Jenkins, for automating and streamlining the software development pipeline. Proficient in using version control systems like Git for effective code management and collaboration. Hands-on experience with containerization technologies such as Docker for building and deploying applications. Expertise in infrastructure as code (IaC) services, including AWS Cloud Formation and tools like Terraform or Open Tofu, for managing and provisioning cloud resources
• Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required.
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies.
• 5+ years of proven experience in developing and implementing Python-based cloud applications and/or machine learning solutions.
• 1+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker.
• Proven experience in application hosting on Kubernetes enlivenments.
• Proficiency in Python software development with strong experience in its ML ecosystem (numpy, pandas, sklearn, tensor flow, etc.), along with solid skills in Linux scripting. Ability to design and implement software using both object-oriented and functional programming paradigms. Basic knowledge of Java and Groovy is a plus.
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies.
• Solid experience in Agile methodologies (Kanban and SCRUM).