EuropeAI Applied Scientist Intern
11 мес. назад
EuropeWorldwideTraineeOnsite
deep learningstatistical analysismachine learningdata analysis
Internship role focused on designing and implementing applied AI systems for real-world business impact involving deep learning and statistical analysis.
О компании
- Our AI team operates at the intersection of quantitative decision-making and frontier model technology to create real-world impact in the world's foremost companies. They design, build, and implement applied AI systems that improve the quality of human decisions and unlock major efficiencies. The team collaborates with software engineers and data scientists to solve complex problems in inference optimization, scalable systems design, and human-computer interaction. They combine technical deep learning, business acumen, and engineering expertise with an entrepreneurial mindset driven by rapid experimentation, first-principles thinking, and a passion for tackling complex real-world problems to deliver lasting impact. As an applied scientist intern, you will identify the most impactful p
Будет плюсом
- Cloud Infrastructure
- Git
Другое
- A degree in computer science, mathematics, statistics, physics, economics, or similar fields from a leading university
- In-depth understanding of mathematical and statistical concepts behind the most common machine learning techniques
- Familiarity with frontier lab APIs (Gemini, OpenAI, Anthropic), and their advanced features like structured outputs and tool calling
- Understanding of LLM inference considerations e.g. input vs. output tokens, prompt caching
- Experience working with deep learning models within natural language processing or computer vision (e.g. HuggingFace model import/fine-tuning /inference)
- Experience writing code in Python
- Experience and willingness to work through the challenges associated with large, unstructured, real-world data sets in a client-facing setting
- Ability to see solutions and opportunities that others do not see
- High level of commitment and reliability, good balance of pragmatism and perfectionism