ML Ops + Python

As an ML/Ops Engineer at our company, your role will involve analyzing, designing, developing, and managing data pipelines to release scalable Data Science models. You will be responsible for deploying, monitoring, and operating production-grade AI systems in a scalable, automated, and repeatable manner. **Key Responsibilities:** - Create and maintain scalable code for delivering AI/ML processes. - Design and implement pipelines for building and deploying ML models. - Design dashboards for system monitoring. - Collect metrics and set up alerts based on them. - Design and execute performance tests. - Perform feasibility studies/analysis with a critical perspective. - Support and troubleshoot issues with data and applications. - Develop technical documentation for applications, including diagrams and manuals. - Work on various software challenges while ensuring simplicity and maintainability within the code. - Contribute to architectural designs of large complexity and size, potentially involving multiple distinct software components. - Collaborate as a team member, fostering team building, motivation, and effective team relations. **Qualification Required:** - Demonstrated experience and knowledge in Linux and Docker containers - Demonstrated experience and knowledge in some main cloud providers (Azure, GCP, or AWS) - Proficiency in programming languages, specifically Python - Experience with ML/Ops technologies like Azure ML - Experience with SQL - Experience in the use of collaborative development tools such as Git, Confluence, Jira, etc. - Strong analytical and logical thinking capability - Proactive attitude, resolutive, teamwork skills, and ability to manage deadlines - Ability to learn quickly - Agile methodologies development (SCRUM/KANBAN) - Minimum work experience of 6 years with evidence - Ability to maintain fluid communication in written and oral English Please note that the following are preferred qualifications: - Demonstrated experience and knowledge in unit and integration testing - Experience or Exposure with AI/ML frameworks like PyTorch, Onnx, Tensorflow - Experience designing and implementing CI/CD pipelines for automation - Experience designing monitoring dashboards using tools like Grafana or similar Join us in our dynamic environment where you will be challenged with various technological tasks and encouraged to enhance your skills in ML/Ops and data science.,