Senior Data Scientist - NLP/LLM

About The Role

Data scientists at Disney Streaming Services are the insights and modeling partners for the growth, content, marketing, product, and engineering teams at Disney+, Hulu and ESPN+. They use data to empower decision-makers with information, predictions, and insights that ultimately influence the experiences of millions of users worldwide. Scientists on the team build models, perform statistical analysis, and create visualizations to provide scalable, persistent capability that is iteratively improved through direct interaction with cross-functional business partners.

As a Senior Data Scientist on the Segmentation and Content Understanding team, you will lead technical efforts in developing and deploying advanced NLP and Large Language Model (LLM) solutions to enhance user experience across Disney+, Hulu, and ESPN+. This role requires expertise in deep learning model architectures, fine-tuning, customization of open-source models, and hands-on experience deploying production-grade AI solutions.

Key Responsibilities

• Develop and deploy advanced NLP and LLM solutions.

• Customize and fine-tune foundational models such as BERT, GPT, and CLIP.

• Create multimodal AI systems integrating text, image, and video data.

• Optimize model performance (accuracy, latency, scalability) leveraging GPU infrastructure and distributed computing.

• Deploy models and manage their lifecycle in production environments.

• Implement robust CI/CD workflows and job orchestration for ML systems.

• Follow software development best practices, including testing, code reviews, and continuous integration.

• Champion and implement MLOps practices for seamless deployment and monitoring.

Basic Qualifications

• Bachelors degree in Computer Science, Engineering, Mathematics, or related field.

• 5+ years of hands-on experience developing and deploying machine learning models in production environments.

• Strong expertise in Deep Learning, NLP, large language models, embeddings, and related technologies.

• Familiarity with transformers, attention mechanisms, multimodal models, and tokenization.

• Proficient with Python, at least one of the deep learning frameworks (such as PyTorch or TensorFlow), and deep learning libraries (such as Hugging Face Transformers).

• Hands-on experience with fine-tuning techniques and model optimization.

• Solid understanding of hardware optimization, GPU usage, and performance trade-offs.

• Proficiency in CI/CD processes, job orchestration tools, Docker, containerization, and MLOps workflows.

• Excellent communication skills, capable of clearly articulating technical concepts to non-technical stakeholders.

• Comfort working in fast-paced environments, adapting proactively to changing priorities.

Preferred Qualifications

• Master’s degree in Computer Science, Engineering, Mathematics, or related field.

• Experience using vector databases and retrieval systems.

• Familiarity with GPU profiling and memory optimization for large models.

• Familiarity with NLP techniques such as RLHF, parameter-efficient tuning, and retrieval-augmented generation (RAG).

Additional Information

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