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Browse vetted remote FastAPI positions — model serving APIs, LLM backend engineering, and production inference systems at companies shipping real AI products.
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Clinical notes are where 80% of medically relevant information lives — and 0% of it is machine-readable without significant NLP work. A cardiologist's...
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Our chatbot platform serves 340 enterprise clients, and every client needs training data that reflects their specific domain, tone, and use cases. A h...
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A Fortune 500 company's legal team manages 4,000 active contracts simultaneously. Buried in those contracts are thousands of obligations: reporting de...
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Our analytics platform serves 280 mid-market companies whose data teams are a single analyst or, frequently, zero. These companies have BI dashboards,...
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GDPR consent management sounds like a checkbox problem until you're running a data platform serving 14 EU markets with 6 different lawful bases for pr...
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Posted 4 months ago
United States — Los Angeles (UTC-7)
We manage ML infrastructure for 28 AI companies that don't want to hire dedicated platform teams. Our platform monitors their training clusters, flags...
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Deploying AI models is not like deploying software. A model that passes all unit tests can still regress on edge-case inputs, behave differently acros...
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We generate docstrings for 300,000 Python functions per month for software companies that want their codebases documented automatically. The generatio...
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Location data becomes powerful when you can act on it in real time. A customer walking into a competitor's parking lot. A delivery truck detouring off...
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The best ad creative in the world fails if it reaches the wrong person at the wrong moment. Our clients are DTC brands running 50-200 active ad varian...
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Role guide
FastAPI has become the default framework for serving AI models and LLM applications in Python, largely because its async support and automatic validation fit naturally with inference workloads. Remote FastAPI jobs at AI companies usually mean building the API layer between a model and the rest of a product — handling streaming responses, request batching, and production reliability, not just wrapping a model in an endpoint.
What remote FastAPI jobs are posted on RemoteAI?
Mostly AI backend and model-serving roles — building the API layer for LLM products, ML inference endpoints, and internal tooling that connects models to the rest of a product. Most require production Python experience beyond basic CRUD APIs.
Why do AI companies prefer FastAPI over Flask or Django?
Native async support handles the I/O-bound nature of model inference and streaming LLM responses well, and built-in Pydantic validation reduces boilerplate for the structured request/response formats AI APIs typically need.
Do FastAPI jobs require ML experience, or just backend skills?
It varies. Some roles are pure backend engineering — you serve models built by others. Others expect you to understand model behavior well enough to design sensible APIs around it (batching, timeouts, streaming). Check individual listings for the split.
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