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.