About the company
The Nexus Project is a scientific and engineering effort bringing truth to the field of computation. We’re enabling a new form of compute: verifiable computation, powered by open science and open-source software so it can benefit everyone. Our work aims to bring to life decades of advancements in zero-knowledge cryptography, achieved by many scientists, engineers, and mathematicians, into a single software system. Nexus raised $25M in Series A funding, co-led by Lightspeed and Pantera, with participation from Dragonfly, SV Angel, and more. Our team consists of some of the world's top cryptographers, mathematicians, and engineers, all working together with one goal: to unite the world's computers and prove humanity's computations.
Job Summary
Responsibilities
📍Design & build the core systems and services that power our AI products, ensuring they are scalable, secure, and highly performant. 📍Develop and optimize machine learning pipelines (from data ingestion to training and real-time inference) to deliver AI features quickly and reliably. 📍Integrate new machine learning models into production applications, working closely with ML engineers to turn prototypes into rock-solid services. 📍Monitor and improve system performance and reliability in production – you'll debug issues, tweak performance, and ensure our infrastructure can grow with our user base. 📍Collaborate with a small, cross-functional team (ML engineers, data scientists, product managers) to brainstorm ideas, plan projects, and rapidly ship new features. 📍Rapidly prototype new ideas and experiments to push the boundaries of our AI capabilities – we love quick iterations and learning by doing. 📍Maintain quality: Write clean, maintainable code with proper tests, and participate in code reviews to keep our codebase top-notch.
Responsibilities
đź“Ť3+ years of hands-on software development experience, with a focus on building and scaling backend systems (bonus if some of that is with AI or data-intensive applications). đź“ŤStrong coding skills in Python, C++, or similar languages, and solid computer science fundamentals (data structures, algorithms, etc.). đź“ŤExperience with AI/ML: Familiarity with machine learning frameworks (e.g. PyTorch, TensorFlow) and a good understanding of how ML models work. đź“ŤCloud & DevOps savvy: Experience deploying applications on cloud platforms (AWS, GCP, etc.) and using containers/orchestration (Docker, Kubernetes) to build scalable systems.
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