remote
Staff Deep Learning Engineer - NBCUniversal
ML Engineer
Lead the design and deployment of large‑scale deep learning models for media and streaming products, leveraging Python, TensorFlow/PyTorch, CUDA acceleration, and cloud infrastructure.
About the role
Key Responsibilities
- Architect, develop, and productionize state‑of‑the‑art deep learning models for video, recommendation, and content analysis pipelines.
- Design scalable training workflows using distributed GPU clusters and cloud services (AWS) to handle petabyte‑scale media datasets.
- Collaborate with product, data engineering, and research teams to translate business needs into robust AI solutions.
- Mentor senior and junior engineers, establish best practices for model versioning, monitoring, and continuous integration.
- Stay current with emerging research in computer vision, natural language processing, and multimodal learning, and evaluate their applicability to the business.
Requirements
- 5+ years of hands‑on experience building and deploying deep learning models in production, preferably in media or streaming domains.
- Strong proficiency in Python and deep learning frameworks such as TensorFlow or PyTorch, with extensive experience in CUDA‑accelerated GPU programming.
- Demonstrated ability to design and operate distributed training pipelines on cloud platforms (AWS, SageMaker, or similar).
- Solid understanding of data engineering concepts, large‑scale data processing, and model serving architectures.
- Proven track record of leading technical projects, mentoring engineers, and delivering high‑impact AI solutions.
Skills
pythontensorflowpytorchcudaawsmachine learning