Data Scientist ( LLM MLOps ) $150K - $175K San Francisco CA

Grorapid Labs; San Francisco (CA); Remote; USD 172,000 - 203,000; Full time

Job summary

A startup in San Francisco seeks a Data Scientist to innovate within LLM frameworks and streamline data insights. This role emphasizes building reliable AI systems, deploying APIs, and ensuring data integrity, perfectly suited for proactive and experienced candidates.

Qualifications

• 3-5 years of experience with Python and related tools.
• Experience building and deploying APIs with FastAPI.
• Practical use of LLMs for data tasks is a must.

Responsibilities

• Transform raw data into insights using various tools.
• Train and optimize models for performance.
• Monitor data drift and ensure system reliability.

Skills

Python

Data Visualization

API Development

Machine Learning

SQL

CI/CD

Tools

FastAPI

Pydantic

pandas

PyTorch

TensorFlow

DuckDB

Job description

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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 Technology

• Industries

  Software Development

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