SRE ML focus

Immediate need for a talented SRE ML focus. This is a 06+months contract opportunity with long-term potential and is located in Austin,TX / Sunnyvale, CA(Remote). Please review the job description below and contact me ASAP if you are interested.

Job ID: 26-24296

Pay Range: $48/hr - $50/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).

Key Responsibilities:

• Design and implement cloud solutions, build MLOps on cloud (AWS or Google Cloud Platform)
• Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Flux, Kustomize, Circle CI, Airflow or similar tools
• Data science model containerization, deployment using docker, VLLM, Kubernetes
• Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
• Data science models testing, validation and tests automation
• 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

Key Requirements and Technology Experience:

• Key skills; Python scripting, MongoDB, API integrations
• 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 or Google Cloud Platform)
• 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

Our client is a leading IT Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.

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