ZeroEntropy

ZeroEntropy is building the next-generation retrieval engine for AI systems. We’re rethinking search from the ground up: faster, more accurate, and built to serve as infrastructure for the next decade of AI. As a Founding AI Engineer, you’ll work across research and engineering to design, train, and optimize machine learning systems that push the limits of what’s possible in performance-critical environments. This is a hands-on role for someone who thrives in ambiguity, understands both the math and the machine, and wants to build core technology, not just use it. You’ll join an early, elite team where your ideas will directly shape the product and architecture. This job is for you if: You’ve trained and deployed large models in production and debugged the weird edge cases. You’ve implemented research papers from scratch and made them faster, cleaner, and more accurate. You care as much about the quality of the data pipeline as the model itself. You’re comfortable designing experiments, interpreting noisy graphs, and making decisions under uncertainty. You love making beautiful, clean, type-safe code, with the goal of pure functional programming using algebraic data types, and can drop down to C++/CUDA when performance demands it. You understand distributed systems and what it takes to scale training and inference pipelines in the real world. You want to build a system from the ground up with minimal abstraction and maximum control. Requirements: Deep experience with ML frameworks, experiment tracking, and distributed training. Strong foundation in math and CS fundamentals: linear algebra, probability, optimization, algorithms, data structures, and time complexity. Experience building and scaling robust data and training pipelines. Proficient in Python, with bonus points for C++, Rust, CUDA, or other performance-oriented tools. Comfortable with Linux, containers, and working close to the metal when needed. Bonus: Experience with model compression, quantization, or inference optimization. Background in information retrieval, NLP, or LLM internals. Familiarity with type-safe functional programming languages (e.g. OCaml, Haskell, SML). About the role Based in San Francisco or willing to move there. Very competitive compensation, equity, and benefits. Next Steps: In a quick sentence, write the most impressive thing you've ever done—feel free to brag! Sign up at https://dashboard.zeroentropy.dev/, and let us know how you would build this API from scratch in detail. We are not looking for GPT answers, we are looking for thoughtful responses on how you would build a state-of-the-art search engine to understand how you think and problem solve. Submit your response along with your resume as a PDF when applying.

We are looking for a highly skilled AI Developer to join us on our mission to build the future of search. As the founding engineer, you'll shape the foundation of a high-impact technology with a scrappy but rigorous, and a product-led growth mentality. You will have the autonomy to build, iterate quickly, experiment, and research at the forefront of AI technologies. Your curiosity to learn and growth mindset will help you excel as a hands-on builder who loves to roll up your sleeves and think out of the box to innovate on a core technology needed by all developers building in AI. This job is for you if: You love to disassemble a C++/Rust program and trace through every single nanosecond of CPU usage in order to squeeze the very last drop of performance out of the machine. You know and understand Linux syscalls at a deep level, you look through glibc code, you can debug CUDA code. You understand theoretical foundations in mathematics and computer science, including combinatorics/number theory/abstract algebra. You love making beautiful, clean, type-safe code, with the goal of pure functional programming using algebraic data types; only mutating state where efficiency requires it. Requirements: Extensive experience and proficiency in Rust/C/C++, Python, SML/OCaml, Assembly. Proven experience managing infrastructure with strong Linux, Bash, and SQL skills. Deep understanding of the tech stack down to the metal, including experience with assembly, EVM, graphics shaders, CUDA, or kernel work. Solid grasp of computer science fundamentals like algorithms, data structures, and time complexity, but also knowledge of functional programming concepts like map, filter, and reduce. Familiarity with software design principles and best practices. Experience or willingness to learn about scalability technologies like AWS/Azure, Docker, and Kubernetes. Desire to work with type-safe languages like Rust/Swift (algebraic data types, functional programming, etc). What you will work on: Develop and implement robust features across our platform for high performance and responsiveness. Manage and optimize infrastructure using Linux, Bash, and SQL to ensure system scalability and reliability. Work autonomously on complex projects involving compilers, OS-level work, assembly, and more. Contribute to all phases of the development lifecycle, from research to deployment. Creating state-of-the-art ML models, including LLMs for information retrieval, rerankers, embedding models, etc. Creating scalable and low-latency infrastructure for a state-of-the-art search engine / database using Rust and k8s. Talking to customers to understand their needs, and improve on the technology to meet them. About the role Based in San Francisco or willing to move there. Very competitive compensation, equity, and benefits.

ZeroEntropy is building the next-generation retrieval engine for AI systems. We’re rethinking search from the ground up: faster, more accurate, and built to serve as infrastructure for the next decade of AI. We already have serious technical momentum and real usage. Now we want the best developer experience in the category. Clear docs. Beautiful demos. A community that feels alive. Content that engineers actually want to read and share. This role owns that. The role You will be the voice and surface area of ZeroEntropy to developers. You will shape how developers discover us, understand what we do, try the product, and stay engaged. That spans content, community, product feedback loops, and occasional collaborations and events. The exact mix will evolve with what is working, and you will have a lot of autonomy to choose the highest leverage work. What we are looking for This is a technical role. You do not need to be an ML researcher, but you do need strong engineering instincts and comfort going deep. You are likely a fit if you have: Technical background: you can read code, use APIs, build small prototypes, and explain complex systems clearly. Startup appetite: you move fast, operate with ambiguity, and enjoy building the machine while running it. Deep love for developers: you respect developer culture, know what high signal feels like, and genuinely enjoy being in the community. High quality content taste: you can produce writing and demos that are crisp, honest, and technically accurate, not fluffy marketing. Strong communication: you can turn messy technical details into clean narratives, and turn developer feedback into product clarity. Bonus points: You have built or run developer communities before. You have shipped content that consistently reached engineers (blogs, threads, talks, open source, tutorials). You have experience in devtools, infra, ML systems, search, or data tooling. What success looks like Developers quickly understand what makes ZeroEntropy special. Trying the product feels effortless. Content and demos are memorable and widely shared. The community is high signal and growing. Developer feedback consistently translates into product improvements. Location In person in San Francisco preferred. Remote ok.

About Us: ZeroEntropy is building next-generation technology for information retrieval over complex unstructured data. We are a team of engineers and scientists from Berkeley, CMU, Ecole Polytechnique, USACO, and have become experts in information retrieval technologies. We are a well funded startup out of Y Combinator, and have already gained great traction in the last few months. We are looking for a highly skilled intern developer to join us on our mission to build the future of search. What you will work on: Contribute to all phases of the development lifecycle, from theoretical research to deployment. Create state-of-the-art ML models, including LLMs for information retrieval, rerankers, embedding models, etc. Work autonomously on complex projects involving compilers, OS-level work, assembly, but also model architecture, training optimization, and more. Create scalable and low-latency infrastructure for a state-of-the-art search engine / database using Rust and k8s. Talk to customers to understand their needs, and improve on the technology to meet them. Requirements: Proficiency in Rust/C/C++, Python, SML/OCaml, Assembly. Deep understanding of the tech stack down to the metal, including experience with assembly, EVM, graphics shaders, CUDA, or kernel work. Deep understanding of theoretical foundations in mathematics and computer science, including combinatorics/number theory/abstract algebra. Solid grasp of computer science fundamentals like algorithms, data structures, and time complexity, but also knowledge of functional programming concepts like map, filter, and reduce. Familiarity with software design principles and best practices. Experience or willingness to learn about scalability technologies like AWS/Azure, Docker, and Kubernetes. Bonus: any background in math/programming competitions. About the internship Based in person in San Francisco. Small startup where you’ll be working closely with both founders, and exceptionally gifted interns already joining us for the summer.