Remote positions
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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Design tooling should be usable without a dedicated engineering team behind it — that's our mission, and FastAPI, Python, and Docker are the core of w...
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We just closed a wave of new enterprise logos and our sales engineers are now spending more time spinning up demo environments than actually running d...
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Our mission is to give operations teams visibility into contract obligations they currently track in spreadsheets and shared drives. This role turns t...
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You'll be the second automation engineer on a team of five, working directly with the process mining lead who designed our existing workflow architect...
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As a fully async team spread across 9 time zones, we believe great engineers can do their best work without a shared meeting slot — which is exactly w...
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Campaign assets get localized into 18 languages, updated mid-flight, and re-localized again — and right now our creative teams track which version is...
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We believe public records requests shouldn't take county clerks three weeks to fulfill because every document has to be manually redacted for personal...
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PyTorch models come and go on our benchmarking platform, but the documentation describing what each one actually does rarely keeps up, which frustrate...
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As a fully async team spread across 9 time zones, we believe great engineers can do their best work without a shared meeting slot — which is exactly w...
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Campaign assets get localized into 18 languages, updated mid-flight, and re-localized again — and right now our creative teams track which version is...
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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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