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Location:
Remote
Duration:

Permanent

Our Vision

Would you like to work in a team where respect and fairness are the standard, while helping build a cutting edge product that will leverage the best of engineering and data science? With the global datasphere growing exponentially to close to 200 zettabyte by 2025, it is crucial for companies to leverage the data and the latest AI technologies. Our vision is to make this possible with the world's de facto platform for actionable predictive insights.

Location/Timezone

  • Full remote position,
  • Need to be between GMT+1 and GMT+3.

Our Stack

  • Project management: Jira, Slack, Google Workspace, Trello,
  • AWS: Lambda, EC2, EKS, Athena, Glue, SAM, CloudFormation,
  • Golang,
  • Docker,
  • Python Spark and ML (TensorFlow, PyTorch, Optuna …),
  • Git/CICD: GitLab.

Your Work

  • You will work closely with the Engineering and the Data Science team in building/maintaining/optimizing the ZYTLYN Prediction Platform,
  • Optimize the data science workflow by providing ideas and tools (such as Kubeflow),
  • Maintain, optimize and setup best practices for the CICD,
  • Design and setup the monitoring platform,
  • Design and implement security boundaries (VPN, LoadBalancer, Oauth Gateway …),
  • Support the initial launch, deployment, setup, and maintenance of our EKS cluster,
  • Participate in the sprint, help developers and data scientists in designing solutions,
  • Help managing the infrastructure cost,
  • Automate everything.

Your Skills

  • Team work, you are collaborative,
  • Good knowledge of Python or Golang,
  • Proficient with cloud architecture,
  • Significant experience with AWS,
  • Proficient with infrastructure as code (Terraform, CloudFormation, Ansible),
  • Experience with orchestration platform (such as Nomad, Kubernetes),
  • Previous experience in a data centric company and associated tools (such as Spark, Kafka, EMR ...).

Benefits

  • Competitive compensation,
  • Equity in a venture backed and well capitalized Swiss start-up founded by data scientists, engineers and industry experts, passionate about solving tough problems with a global impact,
  • Learning and development support,
  • Flexible working hours and paid leave.