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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Podcasters spend 3 hours post-processing for every hour of content they record: editing out filler words, adding chapter markers, writing show notes,...
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Canary deployments exist to catch problems before they affect 100% of traffic. The problem is that most canary analysis is manual: an engineer watches...
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A thorough prior art search for a software patent application takes a patent attorney 6-15 hours and costs clients $3,000-$8,000. Our platform reduces...
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Legal research has a well-known efficiency problem: junior associates at law firms spend 40-60% of their billable hours finding and summarizing cases....
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We serve 120,000 developers who use our AI platform to build production applications. Our documentation is good. Our tutorials are passable. But our i...
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We publish internally and encourage conference submissions. The person in this role will be expected to stay current with TTS research, implement find...
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Accessibility compliance testing today is largely manual: designers run through checklists, QA engineers test screen readers, and accessibility consul...
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We build AI tutoring tools for university students. Our platform generates practice problems, provides step-by-step explanations, adapts difficulty ba...
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We wrap AI models in production-ready APIs. Our clients train models — we handle everything else: authentication, rate limiting, versioning, monitorin...
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Compliance officers at banks spend 60% of their time on document review — reading through transaction reports, client disclosures, and regulatory fili...
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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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