Company Description NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing current pathways to growth. 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.

We are seeking a highly skilled GenAI MLOps Engineer to join our AI Engineering team. In this role, you will design, build, deploy, and operate the core infrastructure powering our Generative AI and Machine Learning solutions. You will collaborate closely with Data Scientists, AI Engineers, Platform Engineers, and Software Development teams to productionize LLM-based applications, automate workflows, optimize infrastructure, and ensure scalable, secure, and cost-effective AI operations.

The ideal candidate possesses strong expertise in cloud-native MLOps, model deployment, CI/CD automation, Kubernetes, Infrastructure-as-Code, and modern GenAI orchestration frameworks.

ML Pipeline Engineering & CI/CD

Design, build, and maintain end-to-end ML pipelines covering:

Data ingestion

Data preprocessing

Model training

Deployment

Monitoring

Azure ML Pipelines

Vertex AI Pipelines

Azure DevOps

Automate code quality checks, security scanning, testing, model validation, and deployment processes.

Model Deployment & Serving

Containerize AI/ML workloads using Docker.

Deploy and manage ML inference workloads on:

Kubernetes (AKS/EKS/GKE)

Cloud-native AI services

Implement advanced deployment strategies including:

Canary deployments

Blue-Green deployments

Shadow deployments

A/B testing

Support deployment of LLMs, RAG systems, and AI agents into production environments.

Monitoring, Observability & Reliability

Implement observability for AI systems through logs, metrics, and distributed tracing.

Datadog

AWS

CloudWatch

Data drift

Performance degradation

Cloud & Infrastructure Engineering

Operate and optimize AI workloads on at least one major cloud platform:

Microsoft Azure

AWS





Google Cloud Platform

Manage AI services such as:

AWS SageMaker

Vertex AI

Networking

Managed AI services

Generative AI Orchestration & Vector Search

Embedding pipelines

Vector database integrations

Work with vector databases including:

Azure AI Search

Implement secure AI deployment practices.

Ensure compliance with organizational security, governance, and data privacy standards.

Support Responsible AI and model governance initiatives.

Cost Optimization & Performance Engineering

Monitor cloud consumption and AI infrastructure costs.

Partner with Data Scientists and AI Engineers to productionize models.

Collaborate with Software Engineering teams to integrate AI services into products.

Deployment guides

On-call support documentation

Establish best practices for AI platform operations and reliability.

5+ years of experience in DevOps, Platform Engineering, SRE, or MLOps roles.

- Minimum 3+ years supporting Machine Learning, Deep Learning, or AI production systems.
- Proficient in Databases specially Graph Db like Neo4j, memgraph (NosQL and SQL)
- Must be able to do Data Modelling
- Must know about Embeddings, Vector Database, Semantic Search
- Must have scripting and automation skills using Python, Golang, Bash, or similar languages.
- Strong hands-on expertise with one major cloud platform (Azure, AWS, or GCP).
- Experience deploying AI/ML workloads at scale.

~ Strong experience with:

- Docker
- Kubernetes
- Proven expertise building CI/CD pipelines.
- Hands-on experience with Infrastructure-as-Code tools.
- Experience with monitoring and observability platforms.
- Vector databases
- Experience working with Azure OpenAI, Amazon Bedrock, or Vertex AI.

Hands-on experience supporting production LLM applications.





Experience with model evaluation frameworks and LLM observability tools.

Knowledge of Responsible AI, AI governance, and security best practices.

Relevant cloud certifications (Azure, AWS, or GCP) are a plus.

Flexible working environment

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. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. 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:

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. 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.

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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. 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. To learn more about our ongoing efforts in diversity and inclusion, please visit the

📌 Database Platform DevOps Engineer (Pune)
🏢 Nielseniq
📍 Pune