Senior Member Technical Staff

Nielsen Holdings Plc; Bengaluru; Sur place; INR 3 500 000 - 5 500 000; Plein temps

Avantages offerts par ce poste

Competitive salary and benefits

Professional growth opportunities

Collaborative and inclusive work环境

Résumé du poste

Gracenote, the content data division of Nielsen, seeks talented engineers to join our ISVI team in Bengaluru. You will build the next-generation metadata platform with a platform-first mindset, enabling machines to understand video content using AI.

You will own end-to-end delivery from design through deployment, collaborating across frontend, backend, and AWS infrastructure. The role emphasizes scalable systems, AI-native development, and mentoring peers within a diverse, global team.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 6–10 years of professional software development experience.
• Strong proficiency in a modern programming language such as Python, Java, or Go.
• Strong computer science fundamentals: data structures, algorithms, concurrency, and distributed systems.
• Solid grasp of RESTful APIs, microservices architecture, and event-driven design.
• Experience across cloud-native development (AWS preferred), containerization and orchestration (Docker, Kubernetes), and CI/CD practices.
• Fluency with an AI-native SDLC, using AI coding assistants and agentic tooling as a core part of how you design, build, and ship.

Responsabilités

• Own problems end to end across the full stack, from frontend and backend to AWS infrastructure and the software–AI boundary.
• Design and operate scalable, reliable systems that process high volumes of video data with speed and accuracy.
• Integrate state-of-the-art foundational and open-weight models (LLMs, VLMs, vision AI) into production pipelines to extract structured understanding from video.
• Ship end to end, iteratively and fast, using AI coding assistants as part of your daily workflow.
• Build cloud-native, event-driven services on AWS with messaging and streaming systems (e.g., Kinesis, SQS) for high-throughput, asynchronous workloads.
• Turn ambiguous problems into clear technical designs and working software.
• Raise the engineering bar, mentor peers and help shape team practices.

Connaissances

Python/Java/Go proficiency

RESTful APIs

Distributed systems

Cloud-native development

CI/CD practices

Formation

Bachelor's or Master's in CS/Engineering or related

Outils

AWS

Docker

Kubernetes

Kinesis/SQS

Description du poste

At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future.

Job Description

Gracenote, the content data division of Nielsen, powers innovative entertainment experiences for leading media companies worldwide. Our advanced entertainment metadata and connected IDs enable seamless content navigation and discovery, helping consumers connect to the content they love and explore new favorites. With a global presence, Gracenote delivers both global and localized video, audio, automotive, and sports content solutions across the Americas, Asia-Pacific, Europe, the Middle East, and Africa. Some of the biggest names who trust Gracenote include Jio, Amazon, NBC, BMW, Mercedes-Benz, Samsung, and Sony.

We are seeking talented engineers to join our Gracenote Tech team, from mid-level to senior. The ideal candidate cares about clean, well-designed code and can independently drive implementation from design through delivery.

Job Purpose:

As a lead engineer on our In-stream Video Intelligence (ISVI) team, you will build the next-generation metadata platform that gives machines a rich, structured understanding of video content, combining strong engineering with state-of-the-art AI. You will create high-performance applications with a platform-first mindset, where scalability, consistency, and reliability sit at the core of every decision.

Key Responsibilities:

Own problems end to end across the full stack, from frontend and backend to AWS infrastructure and the software–AI boundary. We have no pure-play specialists.

Design and operate scalable, reliable systems that process high volumes of video data with speed and accuracy.

Integrate state-of-the-art foundational and open-weight models (LLMs, VLMs, vision AI) into production pipelines to extract structured understanding from video.

Ship end to end, iteratively and fast, using AI coding assistants as part of your daily workflow.

Build cloud-native, event-driven services on AWS with messaging and streaming systems (e.g., Kinesis, SQS) for high-throughput, asynchronous workloads.

Turn ambiguous problems into clear technical designs and working software.

Raise the engineering bar, mentor peers and help shape team practices.

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

6 –10 years of professional software development experience.

Strong proficiency in a modern programming language such as Python, Java, or Go.

Strong computer science fundamentals: data structures, algorithms, concurrency, and distributed systems.

Solid grasp of RESTful APIs, microservices architecture, and event-driven design.

Experience across a range of data stores: relational, NoSQL, graph, and vector databases.

Hands-on experience with cloud-native development (AWS preferred), containerization and orchestration (Docker, Kubernetes), and CI/CD practices.

Fluency with an AI-native SDLC, using AI coding assistants and agentic tooling as a core part of how you design, build, and ship.

Nice to Have:

Experience building and scaling systems at fast-paced startups and/or tech product companies, with real exposure to the complexities of scale.

Applied AI exposure: vector embeddings, LLMs, VLMs, vision AI, and MLOps.

Experience processing large-scale media (video/audio) or other high-volume data pipelines.

What we Offer

Competitive salary and benefits package.

Opportunities for professional growth and development.

A collaborative and inclusive work environment.