Requirements
Educational Background:
- Master s in Data Science or AI
Experience:
- Minimum of 35 years of experience in data science or machine learning roles with a significant understanding of large language models (LLMs) and natural language processing (NLP).
- Proven track record of deploying machine learning models in production environments.
- Previous experience in an AIfocused company
Technical Skills:
- Proficiency in programming languages such as Python R or Scala.
- Experience with machine learning frameworks and libraries including TensorFlow PyTorch or similar.
- Strong understanding of LLMs including experience with models such as GPT BERT or similar.
- Familiarity with big data technologies and tools (e.g. Hadoop Spark).
- Experience with cloud platforms (e.g. AWS Google Cloud Azure) and containerization technologies (e.g. Docker Kubernetes)
Analytical Skills:
- Expertise in statistical analysis data mining and data visualization.
- Ability to derive insights from complex and large datasets.
Soft Skills:
- Excellent problemsolving abilities and attention to detail.
- Strong communication and presentation skills.
- Ability to work independently and as part of a team in a fastpaced environment.
Educational Background: Master s in Data Science or AI Experience: Minimum of 3-5 years of experience in data science or machine learning roles, with a significant understanding of large language models (LLMs) and natural language processing (NLP). Proven track record of deploying machine learning models in production environments. Previous experience in an AI-focused company Technical Skills: Proficiency in programming languages such as Python, R, or Scala. Experience with machine learning frameworks and libraries, including TensorFlow, PyTorch, or similar. Strong understanding of LLMs, including experience with models such as GPT, BERT, or similar. Familiarity with big data technologies and tools (e.g., Hadoop, Spark). Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) Analytical Skills: Expertise in statistical analysis, data mining, and data visualization. Ability to derive insights from complex and large datasets. Soft Skills: Excellent problem-solving abilities and attention to detail. Strong communication and presentation skills. Ability to work independently and as part of a team in a fast-paced environment.