Senior Data Scientist – NLP/LLM
| Company | The Walt Disney Company |
|---|---|
| Location | Seattle, WA, USA, Santa Monica, CA, USA, San Francisco, CA, USA, Glendale, CA, USA, New York, NY, USA |
| Salary | $138900 – $203900 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior |
Requirements
- 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.
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.
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).