Senior MLOps Engineer

NielsenIQ; Chennai; Presencial; INR 1.800.000 - 2.400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible working environment

Wellness plans

Career development opportunities

LinkedIn Learning

Employee Assistance Program

Descripción de la vacante

NielsenIQ in Chennai, India, is seeking a Senior Software Engineer (MLOPS) to design, build, and operate scalable AI/ML solutions in production. You will collaborate with data scientists, software engineers, product owners, and architects to enable rapid delivery of ML and Generative AI capabilities.

The role emphasizes CI/CD automation, cloud-native MLOps, and robust observability, with opportunities to mentor others and influence architecture while adopting best practices.

Formación

• 6+ years of experience in software/ML/platform engineering or MLOps.
• Strong 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 distributed systems, scalability, reliability, and performance optimization.
• Experience with Docker, Kubernetes, 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, Grafana, or Prometheus.

Responsabilidades

• 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 optimise Vector Database technologies such as Azure AI Search, Pinecone, Weaviate, Chroma, Milvus, or equivalent platforms.
• Partner with Data Scientists to operationalise 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 optimisation.
• 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.

Conocimientos

Python

REST APIs

MLOps

Azure ML

Docker

Kubernetes

CI/CD

GitHub Actions

RAG pipelines

Vector DBs

Educación

Bachelor's degree in CS/Engineering

Herramientas

Azure DevOps

Jenkins

Grafana

Descripción del empleo

Senior Software Engineer (MLOPS Engineer) Job Description 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 optimise Vector Database technologies such as Azure AI Search, Pinecone, Weaviate, Chroma, Milvus, or equivalent platforms.
• Partner with Data Scientists to operationalise 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 optimisation.
• 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.

Qualifications

• 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 optimisation.
• 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.

Additional Information

• 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.

Benefits

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

AI Safety and Recruitment Process

NIQ may utilise 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 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 behaviour 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.

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, colour, 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 https://nielseniq.com/global/en/news-center/diversity-inclusion

Experience Level

Senior Level