Basic requirement:
At Sisar, were searching for a competent applicant who is persistent and self-driven. Along with teamwork, the candidate should have the capacity for independent work and be a good cultural fit for the company.
About Us:
We are a pioneering company dedicated to offering options that will revolutionise how businesses boost efficiency. Working with us is a terrific and comprehensive experience for all stakeholders because we offer a wide range of cutting-edge solutions and technology-driven services.
Our vision:
We have been in the Netherlands for the last 7 years and are now expanding to the UK and India. Officially, were going global. We take great pride in hiring the brightest minds from around the world and having a multinational team.
Requirements
Mandatory Skills
- Design and implement cloud solutions, build MLOps on cloud (GCP).
- Build CI/CD pipelines orchestration by GitHub Actions, Airflow, or similar tools.
- Data science models testing, validation and tests automation.
- Exposure to MLOps Open-source packages like Zen ML, Kubeflow, MLFlow etc.
- Communicate with a team of data scientists, data engineers and architects, document the processes.
Roles and responsibilities
- Design and implement cloud solutions, build MLOps on cloud (GCP).
- Build CI/CD pipelines orchestration by GitHub Actions, Airflow, or similar tools.
- Data science models testing, validation and tests automation.
- Exposure to MLOps Open-source packages like Zen ML, Kubeflow, MLFlow etc.
- Communicate with a team of data scientists, data engineers and architects, document the processes.
Benefits
- Great salary package
- Travel allowance
- An open culture where you can express your views
- Excellent Work life balance
- Visa sponsorship
- A great group of like-minded colleagues
- Relocation support
Mandatory Skills Design and implement cloud solutions, build MLOps on cloud (GCP). Build CI/CD pipelines orchestration by GitHub Actions, Airflow, or similar tools. Data science models testing, validation and tests automation. Exposure to MLOps Open-source packages like Zen ML, Kubeflow, MLFlow etc. Communicate with a team of data scientists, data engineers and architects, document the processes. Roles and responsibilities Design and implement cloud solutions, build MLOps on cloud (GCP). Build CI/CD pipelines orchestration by GitHub Actions, Airflow, or similar tools. Data science models testing, validation and tests automation. Exposure to MLOps Open-source packages like Zen ML, Kubeflow, MLFlow etc. Communicate with a team of data scientists, data engineers and architects, document the processes.