Member of Technical Staff (Data Science)

Black Forest Labs

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 We're looking for engineers to build and maintain the engine that powers our mission to develop visual intelligence. From maintaining and scaling clusters, to building research platforms to accelerate the rate of innovation, this team operates with large breadth and depth. We build the systems to make multi-week/month long training possible, to orchestrate resources at scale, and at the same time efficiently, enabling the next breakthrough model. If you’re obsessed with distributed systems at scale, infrastructure reliability, scalability, security, and continuous improvement, this team would be perfect for you. WHAT YOU’LL WORK ON * Maintain research infrastructure, ensuring health, and optimizing components to extract peak performance from the system (both on application, and infrastructure side) * Scale infrastructure to meet growing research demands while maintaining reliability and performance * Collaborate with research teams to deeply understand their infrastructure needs, and design solutions that balance performance with cost efficiency. * Identify and resolve performance bottlenecks and capacity hotspots through deep analysis of distributed systems at scale. * Build and evolve telemetry and monitoring systems to provide deep visibility into infrastructure performance, utilization, and costs across our cloud and datacenter fleets. * Participate in on-call rotations and incident response to maintain system reliability TECHNICAL FOCUS * Python, Bash, Go * Kubernetes * Nvidia GPU drivers, and operators * OTel, Prometheus WHAT WE’RE LOOKING FOR * Experience building or operating large-scale training platforms * Worked with large scale compute clusters (GPUs) * Proven ability to debug performance and reliability issues across large distributed fleets * Strong problem-solving skills and ability to work independently * Strong communication skills and the ability to work effectively with both internal and external partners * Deep knowledge of modern cloud infrastructure including Kubernetes, Infrastructure as Code, AWS, and GCP * Experience with SLURM * Experience building or operating large-scale training platforms 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. If this sounds like work you’d enjoy, we’d love to hear from you. Base Annual Salary: EU €100,000 - €230,000 + Equity US $150,000 - $300,000 + Equity This role is based in our Freiburg / San Francisco office. We operate a hybrid model and cover reasonable travel costs — relocation is encouraged but not required. We do expect a meaningful in-person presence, and we'll discuss what that looks like for your situation during the process.

Black Forest Labs

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. Our models power the tools used by millions of creators, developers, and businesses worldwide, and FLUX is among the most advanced generative systems in the world. 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 Post-training is where a foundation model becomes a product. In this role, you'll own the post-training pipeline for our multimodal models end to end — from data strategy and reward modeling to preference optimization, distillation, and safety tuning — across image, editing, and video. You'll drive measurable gains in model quality, build the infrastructure that lets the whole research team iterate fast, and push the state of the art in what it means to align a generative model to human intent. This is a Staff / Senior IC role. We're looking for someone who has shipped post-training for a frontier model before and wants to do it again. WHAT YOU'LL WORK ON * Own the full post-training pipeline end to end — from data curation and reward modeling through fine-tuning, preference optimization, distillation, safety tuning, evaluation, and deployment * Advance techniques across the post-training stack: SFT, RLHF, RLAIF, DPO, preference learning, and reward modeling to align models with human intent and aesthetic judgment * Work across modalities: text-to-image, image editing, multi-reference, and video post-training * Build personalization and customization capabilities that let users adapt our models to their own creative style * Design and maintain high-throughput fine-tuning and evaluation infrastructure to support rapid iteration across the research team * Identify quality and alignment gaps through rigorous evaluation, then close them through targeted research and engineering   WHAT WE'RE LOOKING FOR * You've owned post-training for a frontier generative model through release (SFT, preference optimization (DPO or RLHF), distillation, safety tuning) with measurable quality wins on human prefs or standard benchmarks * Deep experience across the post-training stack, not just one slice: reward modeling, preference learning, RLHF/RLAIF, and personalization * Comfortable working across modalities: text-to-image, image editing, multi-reference, and ideally video * Strong PyTorch fluency; you write research code that others can build on * Experience with distillation (LADD, DMD, consistency models, or similar) or with building high-throughput eval pipelines is a strong plus * Bias toward shipping: measurable model-quality improvements that reach users, not just papers   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. If this sounds like work you’d enjoy, we’d love to hear from you. Base Annual Salary: EU €130,000-€340,000 + Equity

Black Forest Labs

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. Our models power the tools used by millions of creators, developers, and businesses worldwide, and FLUX is among the most advanced generative systems in the world. 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 We're building the foundation models that power the next wave of visual intelligence — and pretraining is where that work begins. This role sits at the center of our research effort. You'll shape training objectives, architectures, data strategies, and systems behind our joint image, video, and audio foundation models, with a direct line from your research to products used by millions. This is a Staff / Senior IC role. We're looking for someone who has already led pretraining at the frontier and wants to do it again. WHAT YOU'LL WORK ON * Lead large-scale pretraining experiments for our multimodal (image, video, audio) foundation models (architecture, objective functions, scaling strategies) * Develop and evaluate novel ideas across architecture, optimizers, and training algorithms. * Contribute across the full stack: low-level GPU and systems optimizations, research code, and high-level model design * Lead focused research projects independently and drive larger cross-team initiatives WHAT WE'RE LOOKING FOR * You've led or co-owned pretraining for a foundation model (image, video, LLM, or multimodal) that shipped to production or a major release * Own architectural calls that move the model: attention patterns, modulation schemes, loss formulations, tokenization strategies * Deep experience with large-scale distributed training: FSDP/TP/PP, multi-node runs at 500+ GPUs, debugging loss spikes, NaNs, throughput regressions, and silent correctness issues at scale * Strong intuition for architecture and objective design — you've made calls on attention patterns, modulation schemes, or loss formulations that moved a real model * Track record of shipping: top-venue publications (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV) paired with production impact, or unambiguous production wins at a frontier lab * Deep Python and PyTorch proficiency; comfortable reading and modifying low-level training code * Familiarity with visual generative models is a must 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. If this sounds like work you’d enjoy, we’d love to hear from you. Base Annual Salary: EU €130,000-€340,000 + Equity