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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Backend Engineer - AI - **Company:** Stream - **Location:** Eu, France (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Cloud Computing, Code Review, Information Engineering, Github, Python (Programming Language), Machine Learning, Open Source Technology, Performance Tuning, Software Deployment, Toolchain, Backend, Terraform, Data Pipelines - **Published:** August 24, 2026 - **Apply:** https://fr.indeed.com/viewjob?jk=f160617f5dc6d30d ## About the Role * 5+ years of production-level Python engineering experience, with code you have shipped and maintained rather than only prototyped. * Hands-on machine learning experience, specifically with supervised fine-tuning and post-training of models. * Familiarity with the modern fine-tuning and serving toolchain, e.g. Unsloth, Fireworks, Baseten, or equivalents. * Cloud experience with at least one major provider (GCP or AWS), including infrastructure-as-code with Terraform. * Experience running ML-based products in production: not just training models, but owning them through deployment, monitoring, retraining, and iteration against real usage. * Experience designing and operating data pipelines for training and evaluation; a data engineering background is a strong route into this role. * Demonstrated ownership: a track record of picking up ambiguous problems and driving them to a result without waiting for direction. * Strong communication skills and comfort working in a small, distributed, fast-moving team. Preferred * A visible open-source footprint: libraries you have authored or maintained, meaningful GitHub activity, or contributions to AI model repositories. * Experience with Go (all of Stream's APIs use Go, so it helps when interacting with other teams). * Deep understanding of Python's concurrency model and asyncio's limitations in high-throughput systems. * Experience with real-time or low-latency inference systems. * Experience as an early engineer or founder, or otherwise operating at startup pace with an undefined roadmap. ## Description We're seeking a Staff AI Engineer to own model development on our AI team. You'll build, fine-tune, evaluate, and ship the models that run inside Stream's products, end-to-end, from dataset design through to production. As the technical owner, you will drive key decisions independently, shipping models that directly impact systems serving over a billion users., * Own the development, fine-tuning, and evaluation of in-house AI models from dataset design through to production deployment. * Run supervised fine-tuning and post-training experiments, establishing the benchmarks and evaluation harnesses that tell us whether a model is actually good enough to ship. * Build and maintain the data pipelines that feed model training, keeping data quality, labelling, and reproducibility to a high standard. * Take models to production on Stream's serving stack, tuning for latency, cost, and reliability at high volume. * Set the technical direction for an intentionally undefined problem space, deciding what to build, what to test, and what to abandon. * Work across the wider engineering organisation, interfacing with Go-based API teams and infrastructure to get models integrated into the product. * Contribute to the open-source ecosystem where relevant, and share work publicly through code, writing, or community engagement. * Raise the bar on engineering standards across the AI team through code review, mentorship, and pragmatic best practices. ## Related Videos - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Speeding up Web Apps performance with WebAssembly and Emscripten](https://www.wearedevelopers.com/videos/1985-speeding-up-web-apps-performance-with-webassembly-and-emscripten) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What is Software Engineering in the Age of AI?](https://www.wearedevelopers.com/magazine/640-what-is-software-engineering-in-the-age-of-ai) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)