Assist the engineering team in designing, developing, and deploying scalable AI models. Responsibilities include implementing models, optimizing code, and participating in collaboration activities.
DeepInfra is seeking a talented and motivated Software Engineering Intern to join our team. As an intern, you will be working closely with our experienced engineering team to design, develop, and deploy the top open AI models at scale. This is an excellent opportunity to gain hands-on experience in building scalable and efficient software systems, while working on cutting-edge AI models and algorithms.
- Collaborate with the engineering team to design, develop, and test inference solutions for the top AI models.
- Implement and optimize AI models using Python, C++, CUDA, NCCL
- Monitor and maintain the live service.
- Work on feature development, bug fixing, and code reviews to ensure high-quality software delivery
- Participate in daily stand-ups, code reviews, and design discussions to ensure seamless collaboration
- Stay up-to-date with industry trends and advancements in AI and machine learning
- Try new things
- Ship stuff
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related field
- Strong fundamental knowledge in computer science, including data structures, algorithms, and software design patterns
- Proficiency in Python, including experience with AI/ML libraries and frameworks (e.g., NumPy, pandas, SciPy, TensorFlow, PyTorch)
- 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 teamwork skills, with the ability to effectively collaborate with cross-functional teams
- 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.
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