Senior MLOps Engineer

Responsible for analyzing and developing complex software programming to resolve a variety of problems driven
by different technologies. The software must be developed and maintained with high-quality standards and
minimal defects. What we do is to help our research team to put ML models in production, so we work mostly in building Restful applications, training pipelines (mostly in AzureML Databricks), integrating inference codes, and providing tools and patterns for enhancing our MLOps lifecycle.

Job Responsibilities (List the major responsibilities/outcomes expected of this role):
Create and maintain a scalable infrastructure to deliver AI/ML processes, responding to the user requests
in near real time.
Design and implement the pipelines for training and deployment of ML models.
Conducting requirements analysis and preparing specific proposals.
Write complex code to develop scalable, flexible and user-friendly applications across the full stack of
technologies.
Develop secure and highly performant services and APIs.
Use distributed computing to validate and process large volumes of data to deliver insights.
Perform feasibility studies/analysis with a critical point of view.
Support in the maintenance (troubleshoots software and/or application problems) and evolutionary
development.
Maintain technical documentation of computer applications, diagrams and manuals.
Working on many different software challenges always ensures a combination of simplicity and
maintainability within the code.
Contribute to architectural designs of large complexity and size, potentially involving several distinct
software components.
Working closely with developers, testers and a variety of end users (across different cultures) to ensure
technical compatibility and user satisfaction.
To work as a member of a team, encouraging team building, motivation and cultivating effective team
relations.

E=essential, P=preferred.
E - Bachelors degree in computer engineering or related field.
E - Excellent knowledge of data structures, algorithms and designing for performance, scalability and availability.
E - Proficient in programming languages: Python
E - Demonstrated experience and knowledge in Distributed systems.
E - Demonstrated experience and knowledge in some of the main cloud providers (Azure, GCP or AWS)
E - Demonstrated experience and knowledge in Linux and Docker containers
E - Strong experience in designing and building multithreaded distributed systems.
E - Demonstrated experience developing REST API
E - Experience with ML/Ops technologies like Azure ML Databricks
E - Ability to design and develop relational databases which include writing efficient and well performing SQL, such
Copyright 2025 NIQ. Confidential and proprietary. 2
as PostgreSQL.
E - Experience in the use of collaborative developing tools such as: Git, Confluence, Jira, etc.
E Experience in CI/CD tools pipelines: Github Actions, Jenkins, Docker, Kubernetes
E - Problem solving capabilities.
E - Strong ability to analyze and synthesize. (Good analytical and logical thinking capability)
E - Proactive attitude, resolutive, used to work in a team and manage deadlines.
E - Ability to learn quickly.
E - Agile methodologies development (SCRUM/KANBAN).
E - Minimal work experience of 3-5 years with evidence (Mid).
P - Work experience of 7-8 years with evidence (Senior).
P - Knowledge and experience in using LLM models, such as Azure Open AI services, ChatGPT, etc.
P - Experience in the use of Redis Cache
P - Experience in the use of Azure Service Bus (or another distributed queues technology)
P - Ability to keep fluid communication written and oral. (English, both written and spoken)
P - Experience managing a large amount of data: databases, images, etc

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