> Markdown version of [/jobs/ext/2722349-forward-deployed-engineer](https://www.wearedevelopers.com/jobs/ext/2722349-forward-deployed-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed Engineer - **Company:** Sieve Inc. - **Location:** San Francisco, CA, United States - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Python (Programming Language), Tensorflow, Data Processing, Pytorch, Free and Open-Source Software, Data Pipelines - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/member-of-technical-staff-forward-deployed-sieve-9018575 ## About the Role * Comfortable working directly with customers or external teams to translate ambiguous needs into concrete technical systems * Strong Python developer with hands-on experience in PyTorch or similar ML frameworks * Experience building custom algorithms, model workflows, or large-scale data pipelines * Strong intuition for dataset quality, filtering, labeling, evaluation, and edge cases * Able to break customer-level goals down into the models, heuristics, infrastructure, and QA steps needed to deliver * Writes clean, maintainable code and can move quickly without creating brittle systems * Deep passion for video, media technologies, and frontier AI applications * Motivated by delivering end-to-end outcomes, not just training models or writing research code * Bonus: Experience with large-scale video, audio, or multimodal data processing * Bonus: Active contributor to open source projects * Bonus: Experience as an early hire at a startup * In-person at our SF HQ ## Description As a Forward Deployed Engineer at Sieve, you'll work on highly specific dataset problems for frontier AI labs. We're looking for someone with a strong bias to action who likes working closely with customers, untangling messy requirements, and shipping fast. You'll work closely with customers and internal teams to understand exactly what data is needed, then turn ambiguous requirements into production systems that can find, generate, filter, transform, evaluate, and package high-quality video datasets at scale. ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [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) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [AI Vector Search at Scale - Ewa Szyszka - Ewa Szyszka](https://www.wearedevelopers.com/videos/2161-ai-vector-search-at-scale-ewa-szyszka-ewa-szyszka) ## 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) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [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) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)