ML Ops Engineer
ML Ops Engineer
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1 Vacancy
Job Description
Job Summary -
For this role we are looking for ML Ops Engineer with Kubernetes and Python.
Experience Required:
- 6 years of experience in ML Ops with strong knowledge in Kubernetes Python MongoDB and AWS
Technical skills:
- Python Kubernetes Mongo DB Microservices AWS
- SOLR
- ML operations CI/CD pipelines LLM
- 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 MS Azure or GCP)
Qualifications:
- 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
Behavioral Skills:
- Excellent Communication skills and collaboration skills
- Ability to propose and implement improvements in the system
- Ability to work with cross-functional stakeholders
Employment Type
Full-time
