Staff Machine learning Engineer

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

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