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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Tuvex Solutions processes 40,000+ customer support tickets per month for enterprise SaaS clients. Right now, ticket routing is mostly rule-based — a p...
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Posted 3 months ago
United States — Chicago (UTC-5)
Navio Tech builds the developer experience layer that makes AI APIs approachable for engineers who aren't ML experts. One of our core challenges: ever...
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Quelva Works builds workflow automation tools used by enterprise operations teams in insurance, financial services, and healthcare. In these industrie...
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Posted 3 months ago
United States — New York (UTC-4)
Session-based recommendation addresses the cold-start limitation of collaborative filtering: when a new user arrives or an existing user starts a fres...
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A/B testing one creative element at a time is slow. Multivariate testing — testing multiple elements simultaneously (headline, image, call-to-action,...
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An API platform's health is determined not just by its own uptime and latency but by the health of the ecosystem built on top of it. A partner integra...
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Posted 3 months ago
United States — Chicago (UTC-5)
On-call engineers are woken up at 2am to respond to alerts. If those alerts are noisy — firing on transient issues, firing on things that resolve them...
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Posted 3 months ago
United States — Chicago (UTC-5)
Online feature stores serve model inference in real time. When a feature goes stale — when the last successful update is 4 hours ago for a feature exp...
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Dyslexia affects 10-20% of the population and is the most common reading disability. Content formatted for typical readers — dense paragraphs, complex...
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Semantic role labeling — determining who did what to whom, when, where, and how in a sentence — is the NLP task that connects surface syntax to event...
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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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