As a Senior MLOps Engineer, you will collaborate with Data Scientists, Software Engineers, Product Owners, and Architects to design, build, deploy, and operate scalable AI/ML solutions in production. You will drive the adoption of engineering best practices, CI/CD automation, and cloud-native MLOps capabilities while enabling rapid delivery of Machine Learning and Generative AI solutions.

Key Responsibilities

• Design and maintain scalable MLOps infrastructure and platforms for AI/ML workloads.
• Develop and maintain RESTful APIs and backend services using Python.
•  Build and automate ML training, deployment, monitoring, and retraining pipelines using Azure ML.
• Design and implement CI/CD pipelines using GitHub Actions and related DevOps tools.
• Deploy and manage containerized workloads using Docker and Kubernetes.
• Implement monitoring, logging, alerting, and observability solutions for applications and ML models.
• Develop and support RAG (Retrieval-Augmented Generation) solutions, including embedding generation, semantic search, and vector retrieval.
• Integrate and optimize Vector Database technologies such as Azure AI Search, Pinecone, Weaviate, Chroma, Milvus, or equivalent platforms.
• Partner with Data Scientists to operationalize ML, LLM, and Generative AI solutions.
• Troubleshoot production issues involving applications, infrastructure, data pipelines, and ML models.
• Contribute to architecture design, scalability planning, and performance optimization.
• Drive engineering excellence through code reviews, automated testing, coding standards, and secure development practices.
• Establish best practices for unit testing, integration testing, performance testing, and release management.
• Mentor engineers and promote modern software engineering and MLOps practices.
• Evaluate new technologies, frameworks, and tools to improve platform capabilities.
• Create and maintain technical documentation, architecture diagrams, and 
  operational runbooks.

• 6+ years of experience in Software Engineering, Data Engineering, Platform 
• Engineering, or MLOps.
• Strong hands-on expertise in Python and REST API development (FastAPI/Flask).
• Experience building RAG pipelines and LLM-powered applications.
• Hands-on experience with embedding models and semantic search architectures.
• Experience building and operating ML workflows using Azure ML or similar 
• platforms.
• Strong understanding of data structures, distributed systems, scalability, reliability, 
• and performance optimization.
• Experience with Pandas, NumPy, SQLAlchemy, and data processing frameworks.
• Strong SQL and database experience across relational and NoSQL technologies.
• Experience with Docker, Kubernetes (AKS preferred), and Linux environments.
• Experience implementing CI/CD pipelines using GitHub Actions, Azure DevOps, 
• Jenkins, or similar tools.
• Hands-on experience with Git, GitHub workflows, branching strategies, and 
• repository management.
• Experience with monitoring and observability tools such as Azure Monitor, 
• Application Insights, Grafana, or Prometheus.
• Experience with cloud platforms, preferably Microsoft Azure.
• Strong understanding of messaging and event-driven architectures such as Kafka 
• or Service Bus

• Enjoy a flexible and rewarding work environment with peer-to-peer recognition platforms.
• Recharge and revitalize with help of wellness plans made for you and your family.
• Plan your future with financial wellness tools.
• Stay relevant and upskill yourself with career development opportunities.

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

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Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence.  All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion