Member of Technical Staff - Model Serving / API Backend Engineer

Bflai — Germany · Posted ~23 hours ago

Skills

API Development Model Serving Backend Engineering Inference Optimization Scalable Systems API Machine Learning

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Summary

Develop backend systems that expose advanced AI capabilities through reliable APIs while optimizing inference performance and production scalability.

Highlights

Help productionize advanced AI models by building scalable APIs and high-performance inference infrastructure.

Description

About Black Forest Labs We're the team behind Latent Diffusion, Stable Diffusion, and FLUX—foundational technologies that changed how the world creates images and video. We’re creating the generative models that power how people make images and video—tools used by millions of creators, developers, and businesses worldwide. Our FLUX models are among the most advanced in the world, and we're just getting started. Headquartered in Freiburg, Germany with a growing presence in San Francisco, we're scaling fast while staying true to what makes us different: research excellence, open science, and building technology that expands human creativity. Why This Role Our research team moves fast. Models improve weekly. New capabilities emerge constantly. What slows us down is not model quality—it’s productionization. Without this role: Research checkpoints sit longer before becoming usable APIsInference is slower than it needs to beAPIs struggle under loadDemos don’t reflect the true potential of our models This role removes the bottleneck between frontier research and production reality. Once hired, researchers ship faster, demos launch faster, and customers experience models at their best. What You’ll Work On You will own the bridge between research breakthroughs and production systems. Turn research checkpoints into production-ready inference servicesDesign and maintain high-performance APIs serving millions of requestsOptimize inference latency and throughput across GPU infrastructureBuild scalable serving architectures that handle unpredictable trafficImprove reliability, monitoring, and observability across model-serving systemsPrototype and ship demos that showcase new capabilities in days, not weeksCollaborate closely with researchers to move from idea to live endpoint rapidly Tools & Context – Model Serving & API Infrastructure Python, FastAPI, async systemsGPU infrastructure, CUDA, inference optimizationDocker and KubernetesRedis, Postgres, distributed task queuesCloud platforms (AWS, GCP, or Azure)Observability stacks (metrics, logging, tracing) This role spans backend systems, GPU performance, and production ML serving. What We’re Looking For You’ve built and operated systems at meaningful scale. You understand the difference between a research prototype and a production system. You are comfortable navigating ambiguity, making tradeoffs, and improving systems under real-world constraints. You demonstrate: Strong judgment around performance, reliability, and cost tradeoffsExperience scaling APIs or ML systems under loadComfort working in fast-moving, research-adjacent environmentsOwnership from system design through debugging and deployment Role-specific experience we value: Building and operating ML inference services in productionDesigning scalable API architectures with async processingOptimizing GPU workloads (batching, quantization, compilation, CUDA)Managing distributed systems and task queues under variable loadImplementing monitoring and observability for production ML systemsDebugging performance bottlenecks across model, infrastructure, and network layers Bonus experience includes: Real-time or low-latency inference systemsTensorRT, reduced precision, layer fusion, or model compilation techniquesFrontend demo tooling (Streamlit, Gradio, React)CI/CD and automated testing for ML systemsSecurity best practices for API and model serving How We Work Together We’re a distributed team with real offices that people actually use. Depending on your role, you’ll either join us in Freiburg or SF at least 2 days a week (or one full week every other week), or work remotely with a monthly in-person week to stay connected. We’ll cover reasonable travel costs to make this possible. We think in-person time matters, and we’ve structured things to make it accessible to all. We’ll discuss what this will look like for the role during our interview process. Everything we do is grounded in four values: Obsessed. We are a frontier research lab. The science has to be right, the understanding deep, the product beautiful. Low Ego. The work speaks. The best idea wins, no matter who said it. Credit is shared. Nobody is above any task. Bold. We take the ambitious bet. We ship, we do not wait for conditions to be perfect. Kind. People over politics. We treat each other with genuine warmth. Agency without empathy creates chaos. Base Annual Salary: $180,000–$300,000 USD We're based in Europe and value depth over noise, collaboration over hero culture, and honest technical conversations over hype. Our models have been downloaded hundreds of millions of times, but we're still a ~50-person team learning what's possible at the edge of generative AI.