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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Full-time roles and fixed-scope freelance missions — matched to your AI skills.
Payment routing sounds simple until you realize there are 14 different processors, each with different fees, approval rates, currency support, and dow...
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Code reviews catch bugs, enforce style, and spread knowledge — but they're also a bottleneck that delays shipping. The average PR waits 18 hours for i...
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Full automation isn't always the goal. For high-stakes decisions — medical diagnoses, legal classifications, content moderation at scale — the right a...
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Customer success teams manage hundreds of accounts and need to prioritize their attention. Which accounts are thriving and don't need hand-holding? Wh...
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Posted 4 months ago
United States — New York (UTC-4)
A test that sometimes passes and sometimes fails for no obvious reason is a flaky test — and it's the bane of every CI/CD pipeline. Engineering teams...
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"Your pronunciation was 73% accurate" is useless feedback. "You pronounced the /θ/ sound in 'think' as /t/ — try placing your tongue between your fron...
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Posted 4 months ago
United States — New York (UTC-4)
Engineers spin up cloud resources and forget about them. A dev database running 24/7 for a project that ended 6 months ago. A GPU instance nobody conn...
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Prior authorization is the process where doctors get insurer approval before providing treatments — and it delays care for 93 million patients per yea...
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Vector databases cache embeddings to avoid recomputing them on every query. The problem is freshness: when source documents change, their cached embed...
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Before deploying a new model version, engineers should know: if this deployment fails, what breaks? Which downstream services depend on this model's o...
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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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