DevOps Engineer

Job Summary

In this role, you will have the opportunity to design and develop solutions, contribute to roadmaps of Big Data architectures, and provide mentorship and feedback to more junior team members. You will help manage the petabytes of data you have and turn them into value. Currently, we are looking for a MLOps/AI Engineer.

Responsibilities

• Design and develop solutions, contribute to roadmaps of Big Data architectures, and provide mentorship and feedback to more junior team members.
• Help manage the petabytes of data and turn them into value.

Tech Stack

• Infrastructure hosted on-prem and in the cloud (Azure and GCP) including MapR, Airflow, Spark, Kafka, Jupyter, Kubeflow, Jenkins, GitHub, Tableau, Power BI, Synapse (Analytics), Databricks and related tools.

Requirements

• University degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Engineering, or related discipline) or equivalent experience.
• Hands on experience in data science, machine learning, or AI engineering, ideally contributing to or leading end to end projects from concept to deployment.
• Strong programming skills in Python (preferred) and solid experience with SQL.
• Familiar with software development best practices (version control, testing, code reviews, CI/CD).
• Proven experience in building backend services, data pipelines, or integrating ML/LLM components into production environments.
• Working knowledge of retrieval and RAG systems, agent orchestration, and solid understanding of the AI/LLM ecosystem and related frameworks.
• Strong understanding of machine learning fundamentals and experience developing and deploying models that deliver real business value.
• Hands on experience with modern ML/AI frameworks (e.g. PyTorch, scikit learn) and good grasp of MLOps workflows for scalable model deployment.
• Experience with cloud platforms (e.g. AWS, Azure, or GCP) and distributed data environments.
• Excellent communication skills in English.
• Ability to clearly explain technical trade offs and decisions to both technical and non technical audiences.
• Awareness of Agile / Scrum ways of working.
• Excellent problem-solving skills and ability to work in a collaborative environment.
• You should have: Github, Kubernetes, Kubeflow, Docker, Python (Preferably ML knowledge), Github Actions / Jenkins, Kibana / Grafrana, Linux/Bash, English - Fluent spoken and written (C1 level).
• In-house training programs: professional and technical training certifications.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.