Software Engineer - Europe, Early Career

What You’ll Do

• Collaborate with engineers to 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 (previous exposure helpful - deep expertise not required).

• Monitor and maintain production model-serving systems.

• Work on new features, fix bugs, and contribute to code reviews.

• Participate in daily standups, design reviews, and team discussions.

• Explore new AI/ML techniques and tools, and experiment with improving model performance.

• Try new things. Ship stuff.

• What You Bring

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field (completed or in final year).

• Strong fundamentals in data structures, algorithms, and software design.

• Proficiency in Python, including experience with AI/ML libraries and frameworks (e.g., NumPy, pandas, SciPy, TensorFlow, PyTorch).

• Experience with AI/ML through coursework, research, personal projects, full-time employment, or internships.

• Familiarity with AI models, Transformers and Diffusers.

• Experience with version control systems (e.g., Git) and agile development methodologies.

• Excellent problem-solving skills, with the ability to debug and optimize code.

• Strong communication and collaboration skills.

• Curiosity, willingness to learn, and desire to build real systems.

• Bonus

• Exposure to 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.

• Req ID: R9