Senior AI Data Scientist

• Should have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Should have solid experience developing and implementing generative AI models, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs.
• Should be proficient in Python and have experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Keras.
• Should have strong knowledge of data structures, algorithms, and software engineering principles.
• Should be familiar with cloud-based platforms and services, such as AWS, GCP, or Azure.
• Should have experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face.
• Should be familiar with data visualization tools and libraries, such as Matplotlib, Seaborn, or Plotly.
• Should have knowledge of software development methodologies, such as Agile or Scrum.
• Should possess excellent problem-solving skills, with the ability to think critically and creatively to develop innovative AI solutions.
• Should have strong communication skills, with the ability to effectively convey complex technical concepts to a diverse audience.
• Should possess a proactive mindset, with the ability to work independently and collaboratively in a fast-paced, dynamic environment

Mandatory Skills:

1. Python knowledge,
2. Basic ML / DL idea
3. Basic knowledge in NLP
4. Understanding on Generative AI
5. Understanding of LLMs (OpenAI focused)
6. Understanding of Langchain
7. LangChain Project/POC experience
8. Understanding of Vector DBs

Good to Have:

1. NLP project experience
2. Cloud (Azure/AWS) ML experience
3. How does GenAI works?
4. GenAI vs Traditional ML
5. Understanding of Semantic Kernel
6. Architecting GenerativeAI solutions
7. Evaluating performance and problems
8. Deployment to Production