Design and implement AI model inference solutions, optimize performance, own production systems, and collaborate in engineering best practices.
About DeepInfra
Why this role matters
What You’ll Do
What You Bring
Bonus
Why DeepInfra
How we work
DeepInfra is building the infrastructure layer for the next generation of AI. We believe open-source models are the future, and companies should have full control over their AI stack without being locked into proprietary providers.
Our inference platform serves trillions of tokens every week across hundreds of production workloads. We build everything from GPU infrastructure to the API layer because every millisecond matters.
We are 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.
- 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
- 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
- Experience with C++, CUDA, or AI inference
- Contributions to open-source ML projects
- 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.
Three traits define the people who thrive here, and this role leans on all three.
Initiative. We take ownership and step in where we can add value. Whether it’s starting something new, improving what exists, or helping move ideas forward, we aim to be proactive and thoughtful in how we contribute.
Drive. We’re energized by hard problems. Building AI infrastructure is complex, and we lean into that. We care about doing things well, moving fast, and continuously improving — because solving meaningful challenges is what motivates us.
Grit. Things don’t always work on the first try — and that’s expected. We stay persistent, adapt quickly, and learn as we go. We take setbacks seriously, but not personally, and use them to get better.
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