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Staff Machine learning Engineer

Haryana, India (Hybrid)

Staff Machine learning Engineer

11 Hours ago • 8 Years + • Research & Development

About the job

5 skills required for this role

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java

python

team-player

scalability

talent-acquisition

Job Description

Nielsen seeks a Staff Machine Learning Engineer to join their Engineering team. The role involves defining, developing, testing, analyzing, and delivering technology solutions within Nielsen's Collections platforms, which support television viewing measurement globally. Responsibilities include owning built ML services (scalability, availability, metrics, alerts, latency), data quality checks, cloud data onboarding, prompt engineering, AI solution architecture, and LLM inference optimization. The engineer will lead ML engineering for a pod and be the technical leader for all ML/AI engineering issues within a delivery pod. Experience leading projects leveraging LLMs, GenAI, and prompt engineering, along with MLOps experience and cloud knowledge, is essential.

Must have:

8+ years software experience
Experience with ML frameworks and models
Own ML services (scalability, availability)
Data quality checks & cloud data onboarding
Prompt Engineering, AI solution architecture
Proficiency in Python and Java

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.

Nielsen is seeking an organized, detail oriented, team player, to join the Engineering team in the role of Staff Machine learning Engineer . Nielsen’s Audience Measurement Engineering platforms support the measurement of television viewing in more than 30 countries around the world. The Software Engineer will be responsible to define, develop, test, analyze, and deliver technology solutions within Nielsen’s Collections platforms.

Qualifications:

Experience having led multiple projects leveraging LLMs, GenAI and Prompt Engineering
Exposure to real-world MLOps deploying models into production adding features to products.
Knowledge of working in a cloud environment
Strong understanding of LLMs, GenAI, Prompt Engineering and Copilot

Responsibilities:

Bachelor's degree in Computer Science or equivalent degree.
8+ years of software experience Experience with Machine learning frameworks and models
The Staff ML Engineer is expected to fully own the services that are built with the ML Scientists. This cuts across scalability, availability, having the metrics in place, alarms/alerts in place – and be responsible for the latency of the services
Data quality checks & onboarding the data on to the cloud for modeling purposes
Prompt Engineering, FT work, Evaluation, Data
End-end AI Solution architecture, latency tradeoffs, LLM Inference Optimization, Control Plane, Data Plate, Platform Engineering
Comfort in Python and Java is highly desirable
The Staff ML Engineer will head the ML engineering for a pod and be the technical leader for all ML/AI Engineering issues in a delivery pod

Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.

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