Site Reliability engineer MLops

Sunnyvale, CA, US • Posted 4 hours ago • Updated 4 hours ago
Contract W2
Contract Independent
12 Months
No Travel Required
On-site
$50 - $55/hr
Fitment

Dice Job Match Score™

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Job Details

Skills

  • MLOps
  • SRE
  • Linux
  • LLM

Summary

Role: SRE – ML focus

Location - Sunnyvale, CA/Austin, TX

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

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 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
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10448332
  • Position Id: UC080626
  • Posted 4 hours ago
Contact the job poster
RK

Raj Kasipally

Recruiter @ Delviom LLC
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