Lead Machine Learning Engineer

Role / Designation : Lead Machine Learning Engineer (Media Tech)

Experience Range : 8+ years

Gracenote, a Nielsen company, is dedicated to connecting audiences to the entertainment

they love, powering a better media future for all people. Gracenote is the content data business

unit of Nielsen that powers innovative entertainment experiences for the world s leading media

companies. Our entertainment metadata and connected IDs deliver advanced content navigation

and discovery to connect consumers to the content they love and discover new ones.

Gracenote s industry-leading datasets cover TV programs, movies, sports, music and

podcasts in 80 countries and 35 languages. Gracenote provides common identifiers that are

universally adopted by the world s leading media companies enabling powerful cross-media

entertainment experiences. Machine driven, human validated best-in-class data and images fuel

new search and discovery experiences across every screen.

Gracenote's Data Organization is a dynamic and innovative group that is essential in

delivering business outcomes through data, insights, predictive & prescriptive analytics. An

extremely motivated team that values creativity, experimentation through continuous learning in

an agile and collaborative manner. The data team oversees the whole data lifecycle from

designing, developing and maintaining data architecture that satisfies our business goals to

managing data governance and region-specific regulations.

Role Overview :

As a Lead Machine Learning Engineer on the Gracenote Media team, you will be responsible for

defining the AI / ML strategy, overseeing large-scale data science projects, and leading teams to

build cutting-edge machine learning solutions that scale content understanding and generation,

entity linkage, and more to achieve the scale that matches our customer s demands.

Key Responsibilities :

Define and execute the AI / ML strategy for content generation (Gen-AI), entity linkage and

matching, image processing, and content understanding.

Lead the development of next-generation content generation systems using Large

Language Models (LLMs)

Architect scalable data platforms to support real-time and batch processing of media-rich

datasets.

Own the Data Quality of the deliverables and ensure the consistent performance of the

models and its output quality.

Define and implement standards for the organization that match industry best practices.

Collaborate with product, engineering, and business teams to drive AI-powered

innovation.

Improve computer vision models for automated content tagging, video summarization, and

understanding.

Oversee MLOps infrastructure to ensure robust deployment and monitoring of ML models.

Stay ahead of emerging trends in AI, deep learning, and media tech, integrating new

research into practical applications.

Mentor and grow a team of data scientists and engineers.

Required Skills :

Expert-level proficiency in Python, SQL, and big data tools (Spark, Kafka, Airflow).

Extensive experience in deep learning, reinforcement learning, NLP, and computer vision.

Experience in large-scale machine learning model deployment and optimization.

Proven leadership skills in building and scaling data science teams.

Experience with Kubernetes, Docker, and cloud AI services.

Qualifications :

Master s in AI, Machine Learning, Data Science, or a related field.

8+ years of experience in data science and machine learning, with at least 3+ years

leading teams.

Strong track record in building AI-driven solutions for media and entertainment.