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About the job
Data Scientist – LLMs, Python, MLOps
Remote | Full-Time
A 2024-founded startup based in San Francisco is building structured data tools to improve the accuracy and reliability of large language models. Their platform powers agentic, RAG-native systems through modular knowledge graphs and developer-friendly APIs, turning unstructured data into useful, trusted knowledge.
What you will do
Turn raw JSON, CSV, or HTML into clean insights. Profile, visualize, and identify patterns or outliers—before anyone asks.
Train and tune models for classification, ranking, and RAG with LLMs to move recall and precision metrics forward every week.
API Integrator
Wrap models using FastAPI, validate inputs with Pydantic, and deploy clean, testable endpoints using CI pipelines.
MLOps Wrangler
Monitor data and model drift, run batch jobs, add simple tests, and ensure long-term system reliability.
Insight Storyteller
Communicate findings through Jupyter notebooks, dashboards, and Loom videos. Make insights clear and accessible to legal and non-technical stakeholders.
Startup Swiss-Army Knife
Take initiative to fix data issues, infra gaps, and edge cases—without waiting for formal tasks or assignments.
You might be a fit if you have
- 3–5 years of experience with Python and tools like pandas, Polars, PyTorch, or TensorFlow
- Experience building and deploying APIs with FastAPI and Pydantic
- Practical use of LLMs for data augmentation or cleaning tasks
- Proficient in SQL, Postgres/DuckDB, and object storage like S3
- Familiarity with CI/CD pipelines (e.g., GitHub Actions)
- You document clearly and share proactively
Bonus if you have
- Experience with web scraping using Scrapy or Playwright, or working with PACER, NHTSA, or FDA datasets
- Familiarity with vector databases like Qdrant or pgvector, and prompt engineering
- Exposure to regulated environments like SOC 2, HIPAA, etc.
Why this role
You’ll work at the core of production-grade AI systems—from structured LLM pipelines to real-time API deployment. Perfect for someone who thrives in fast-moving, high-ownership environments and wants to build meaningful, technical systems that make LLMs safer and more reliable.
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Job function
Engineering and Information TechnologyIndustries
Software Development
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