HI
Greetings
Title: Site Reliability Engineer SRE ML platform
Location:Sunnyvale CA
Type: Full Time/Contract
Onsite Position
JOB DESCRIPTION:
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)
- 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
With Regards
Avinash Chhetri
HI Greetings Title: Site Reliability Engineer SRE ML platform Location:Sunnyvale CA Type: Full Time/Contract Onsite Position JOB DESCRIPTION: Qualifications: 6 years of experience in ML Ops with strong knowledge in Kubernetes Python MongoDB and AWS. Good understanding of Apache SOLR. P...
HI
Greetings
Title: Site Reliability Engineer SRE ML platform
Location:Sunnyvale CA
Type: Full Time/Contract
Onsite Position
JOB DESCRIPTION:
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)
- 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
With Regards
Avinash Chhetri
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