DeepInfra is looking for strong Software Engineers to join our team. You’ll work on designing, building, and scaling infrastructure for serving top open-source AI models in production. This role is ideal for engineers who are already comfortable owning problems end-to-end and want to deepen their experience working on high-impact AI systems. If you’re excited about AI/ML and are looking to work on real systems at scale — we’d love to meet you. What You’ll Do - Design, develop, and test inference solutions for state-of-the-art AI models - Implement, optimize, and evaluate AI models using Python, C++, CUDA, and NCCL - Own and operate production model-serving systems, including monitoring and debugging - Build new features, improve system performance, and contribute to overall system design - Participate in code reviews and technical discussions to maintain high engineering standards - Explore and apply new AI/ML techniques to improve model performance and efficiency - Take ideas from concept to production What You Bring - Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field - 3+ years of relevant experience - Strong fundamentals in data structures, algorithms, and software design - Proficiency in Python and experience working with AI/ML frameworks (e.g., PyTorch, TensorFlow) - Hands-on experience building, shipping, and maintaining software systems - Familiarity with AI models, Transformers, and Diffusers - Experience working with version control (Git) and collaborative development workflows - Ability to debug, optimize, and improve existing systems - Strong communication skills and ability to work independently in a fast-paced environment Bonus - Experience with C++, CUDA, or AI inference - Contributions to open-source ML projects Why DeepInfra - Work on cutting-edge AI model serving - the systems that power the next generation of LLMs and multimodal models. - Small team, huge impact: your work ships directly to customers. - Opportunity to learn from engineers building high-performance inference at scale. - Fast-paced environment with ownership, autonomy, and end-to-end responsibility.

• Develop, deploy and monitor feature computation and analytics services that transform raw biosignal data, machine learning outputs, and clinical metadata to generate meaningful scientific results • Build high-quality composable tooling that enables data scientists to deliver scientific results at scale • Transform custom or semi-standardized data workflows into reusable tools and automated products that power clinical diagnostics and trials • Design, implement, and maintain versioned data models and transformations that enrich biosignal metrics with clinical context • Contribute to reusable, scalable customer-facing analytics products, such as automated scientific reports, dashboards and purpose-specific dataset views • Collaborate closely with teams of engineers, data scientists, and neuroscientists to understand workflow pain-points and inefficiencies that can be resolved with tooling and processes improvements • Partner with scientists, product managers, and stakeholders to identify high-impact analytics improvements that accelerate development of novel therapies and diagnostic tools

• Write performant, maintainable code that is easy to read and well-documented. • Write automated tests to thoroughly validate the correctness of your code. • Deploy large-scale web applications. • Have a focus on quality, and operate iteratively to get from good to better. • Be a part of your team’s on-call rotation; we all own our code end-to-end from development to deployment to operations. • Come ready to learn from some of the best and brightest in the industry. • Work independently and collaboratively in a dynamic and fast-moving team. • Be effective in a team environment working with fellow engineers, product management, and design.

• Design, build, and maintain robust backend systems and APIs deployed in AWS across multiple technical domains • Develop scalable, high-performance solutions that follow modern software design principles and meet business requirements • Contribute to architectural discussions and drive implementation of clean, reusable solutions across services • Ensure the stability, performance, and scalability of core platform services and APIs • Participate actively in Agile ceremonies such as planning, retrospectives, and story grooming • Conduct thorough code reviews, share technical feedback, and contribute to continuous code quality improvements • Collaborate cross-functionally with Product, DevOps, and Security to support high-quality software delivery • Mentor peers and junior engineers through thoughtful collaboration and knowledge sharing.