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Site Reliability engineer MLops

Delviom LLC

Sunnyvale, California • Today

Easy Apply

Contract

50 - 55

Senior Solutions Engineer, AI Infrastructure

VAST Data

Remote or New York • Today

Full-time

Generative AI Operations Engineer (GenAI Ops)

EPAM Systems

Remote • Today

Full-time

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 5 hours ago

Fitment

Dice Job Match Score™

⏳ Almost there, hang tight...

Contact the job poster

Raj Kasipally

Recruiter @ Delviom LLC

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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

Dice Id: 10448332
Position Id: UC080626
Posted 5 hours ago

Fitment

Dice Job Match Score™

⏳ Almost there, hang tight...

Contact the job poster

Raj Kasipally

Recruiter @ Delviom LLC

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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