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Senior specialized ML role in metro location with moderate brand recognition increases applicant density moderately.
Requires specialized computer-vision and generative-model expertise, so cross-industry portability is limited.
Explicit 10+ years, deep ML/CV requirements, and advanced model/production skills enforce strict filtering.
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Lead technical architecture and define long-term AI/ML vision for media understanding and generation within Gracenote's content product ecosystem.
Design and build scalable, multimodal machine learning systems integrating visual, audio, and textual data at petabyte scale.
Oversee and optimize high-performance ML inference systems using advanced techniques and mentor data science and ML engineering teams.
8+ years of relevant work experience, with 10+ years in machine learning and at least 2 years in LLMs or generative image/video models.
Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, Data Science, or related quantitative field required.
Expert-level proficiency in Python, Java, or C++ including multithreading, memory management, and distributed computing frameworks (e.g., Spark, Flink).
Experience with large-scale ML production deployments using Kafka, Airflow, Kubernetes, and cloud AI services (AWS Bedrock, SageMaker).
Experienced in building and architecting complex, scalable, multimodal AI systems for media data including computer vision and generative models.
Able to influence cross-functional and executive stakeholders without formal authority, balancing scientific leadership with strategic vision.
Hands-on expertise with deep learning frameworks (PyTorch/TensorFlow), inference optimization (TensorRT, NVIDIA tools), and MLOps in production-scale environments.