Site Reliability Engineer SRE ML platform

Title: Site Reliability Engineer SRE ML platform
Location: Austin, TX OR Sunnyvale, CA
Type: FTC

Responsibilities:

• Continuous Deployment using GitHub Actions, Flux, Kustomize
• Design and implement cloud solutions, build MLOps on cloud AWS
• Data science model containerization, deployment using docker, VLLM, Kubernetes
• Communicate with a team of data scientists, data engineers and architects, document the processes
• Develop and deploy scalable tools and services for our clients to handle machine learning training and inference.
• Knowledge of ML models and LLM

Qualifications:

• 6+ years of experience in ML Ops with strong knowledge in Kubernetes, Python, MongoDB and AWS.
• Good understanding of Apache SOLR.
• Proficient with Linux administration.
• Knowledge of ML models and LLM.
• Ability to understand tools used by data scientists and experience with software development and test automation
• Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS)
• Experience working with cloud computing and database systems
• Experience building custom integrations between cloud-based systems using APIs
• Experience developing and maintaining ML systems built with open-source tools
• Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes
• Experience developing containers and Kubernetes in cloud computing environments
• Familiarity with one or more data-oriented workflow orchestration frameworks (Kubeflow, Airflow, Argo, etc.)
• Ability to translate business needs to technical requirements
• Strong understanding of software testing, benchmarking, and continuous integration
• Exposure to machine learning methodology and best practices
• Good communication skills and ability to work in a team

Note: Focus is to have 60% SRE and 40% ML Ops