NielsenIQ
Consumer Intelligence
MLOpsEngineer(GenerativeAI)
“MLOps Engineer (Generative AI) at NielsenIQ. Skills: MLOps, Generative AI, Python, Cloud. Design and implement pipelines for ML/AI model training and deployment. Create and maintain scalable code for AI/ML processes”
What You'll Achieve.
Ensure robust engineering and deployment of advanced solutions; Deliver AI/ML processes; Ensure technical compatibility and user satisfaction
Industry & Context.
Problem-solving capabilities; Analytical/logical thinking; Troubleshoot issues with data and applications
What They're Looking For.
Must Have
4+ years of professional experience in software development and/or CI/CD pipeline development, Bachelor’s degree in Computer Science or related field, Proficient in Python programming, Knowledge of OOP, Unit testing, Demonstrated experience and knowledge in Linux, Docker containers, Experience with major cloud providers (Azure, GCP, or AWS), Familiarity with ML/Ops technologies (e. g. , Azure ML), Experience building Agentic pipelines, Experience designing monitoring dashboards (Grafana or similar), Experience with container orchestrators (Kubernetes, Docker Swarm), Experience with AI/ML frameworks (PyTorch, ONNX, TensorFlow), Experience using collaborative development tools (Git, Confluence, Jira, etc. ), Problem-solving capabilities, Analytical/logical thinking, Agile development methodologies (SCRUM/KANBAN), Excellent communication skills in English (written and spoken)
Nice to Have
Master’s degree in Computer Engineering or related discipline, Experience with distributed systems, Knowledge in Power BI, Hands‑on experience building, fine‑tuning, or deploying ML models across domains such as Computer Vision, Natural Language Processing (NLP), and classical machine‑learning methods (e. g. , Decision Trees), Familiarity with modern foundation and open‑source model families such as Qwen, LLaMA, and other large language models (LLMs)
What You'll Do.
Design and implement pipelines for ML/AI model training and deployment
Create and maintain scalable code for AI/ML processes
Respond to user requests in near real time
Design dashboards to monitor system
Collect metrics and create alerts
Design and execute unit and performance tests
Perform feasibility studies/analysis
Support and maintain applications
Troubleshoot issues with data and applications
Develop comprehensive technical documentation
Tackle diverse software challenges
Ensure simplicity and maintainability in code design
Contribute to architectural designs
Work closely with engineers
Ensure technical compatibility and user satisfaction
Work as a member of a team
Encourage team building
Cultivate effective team relations
How You'll Work.
Team & Collaboration
Working closely with other engineers, data scientists and a variety of end-users; Work as a member of a team; Encouraging team building, motivation, and cultivating effective team relations
Communication Scope
Excellent communication skills in English (written and spoken)
Process & Methodology
Agile development methodologies (SCRUM/KANBAN)
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