Applied AI Data Scientist
Builds data-driven solutions and machine learning models for client projects and AI alignment research using Python, LLMs, deep learning frameworks like PyTorch/TensorFlow/JAX. Applies statistical ML, causal inference, and agile methods to deliver impactful products.
About the job
Required Skills and Experience
- Fluency in Python
- Experience with LLM lifecycle: prompt design/engineering, prompting techniques (RAG, few-shot, CoT, etc.), vector databases, multimodality, fine-tuning, and evaluation
- Proven data science experience: key contributor to impactful projects with real-life outcomes
- Statistical & causal ML fundamentals: expertise in experimental design, uncertainty quantification, and rigorous model evaluation across tabular, time-series, and foundation-model fine-tuning tasks
- Deep learning experience: building/training NLP or computer vision models with PyTorch, TensorFlow, or JAX
- Agile & AI-powered development: run lean Kanban/Scrum cycles and leverage AI-powered tools like Cursor to prototype quickly
- Growth mindset: embrace challenges, value progress over perfection
- Self-management: work independently, take ownership
- Product and UX understanding: deliver seamless, user-friendly experience
- Effective communication in English
Bonus Points for
- Self-managed projects: developed from zero and shipped to real users
- Startup experience
- Client relationship management
- Passion for AI alignment
Compensation
- Salary range: $120K to $220K per year for people based in California
- Equity in client projects and Skunkworks ventures
Skills
Python, LLMs, RAG, PyTorch, TensorFlow, JAX, Vector Databases, Prompt Engineering, Fine-Tuning, NLP, Computer Vision, Kanban, Scrum
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