Site Reliability Engineer ML platform - W2

Overview

Title:

Site Reliability Engineer SRE – ML platform

Location:

Austin, TX or Sunnyvale, CA

Employment type:

Full-time
• Seniority:
Mid-Senior level
• ONLY W2

• Continuous Deployment using Git Hub 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

• 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, Data Robot, 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