Have you got what it takes
- Master's degree in the field of Computer Science, Technology, Engineering, Math, or equivalent practical experience
- Minimum of 8 years of data science work experience, including implementing machine learning and NLP models using real-life data.
- Experience with Retrieval-Augmented Generation (RAG) pipelines or LLMOps.
- Advanced knowledge of statistics and machine learning algorithms.
- Proficiency in Python programming and familiarity with R.
- Experience with deep learning models and libraries such as PyTorch, TensorFlow, and JAX.
- Familiarity with relational databases and query languages (e.g., MSSQL) and basic SQL knowledge.
- Hands-on experience with transformer models (BERT, FlanT5, Llama, etc.) and GenAI frameworks (HuggingFace, LangChain, Ollama, etc.).
- Experience deploying NLP models in production environments, ensuring scalability and performance using AWS/GCP/Azure
- Strong verbal and written communication skills, including effective presentation abilities.
- Ability to work independently and as part of a team, demonstrating analytical thinking and problem-solving skills.
You will have an advantage if you also have:
- Expertise with Big Data technologies (e.g., PySpark).
- Background in knowledge graphs, graph databases, or GraphRAG architectures.
- Understanding of multimodal models (text, audio, vision).
- Experience in Customer Experience domains.
- Experience with package development and technical writing.
- Familiarity with tools like Jira, Confluence, and source control packages and methodology.
- Knowledge and interest in foreign languages and linguistics.
- Experience working on international, globe-spanning teams and with AWS.
- Past participation in a formal research setting.
- Experience as part of a software organization.
