Deep InfraSoftware Engineer (Sofia, Bulgaria)
Sofia, Bulgaria · Full-time
€5K–€8K/mo
Series B · $107M · 165d ago Posted 29d ago
Have your AI draft the answers and brief you on Deep Infra→Why join Deep Infra?
The bet: most AI apps will rent inference by the token, and one cheap, reliable API can serve them all. Should it pay off, Deep Infra becomes the quiet AI inference utility under every app, the way a grid powers a whole city. Palo Alto's $107M Series B, bigger than eight in ten Series Bs this half, is backed by NVIDIA and Felicis, and 13 of 20 open roles sit in engineering.
JustBacked's take, based on Deep Infra's own site and its funding and hiring data.
About DeepInfra
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're growing our Sofia, Bulgaria office and looking for strong Software Engineers to join us on-site, working shoulder-to-shoulder with the team that's building it.
Why this role matters
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
Nice to Have
- 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
How we work
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.