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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