- Good understanding of data science, advanced statistics, signal processing and simulation frameworks
- In depth knowledge of the core programming languages (Python, JavaScript, C/C++, etc.), as well as core AI/ML toolsets and libraries (PyTorch, TensorFlow, etc.)
- Understanding and track record of developing and deploying LLM & Deep learning models, for NLP
- Knowledge of RAG, generative AI/MLtechniques, and Hybrid models are a plus.
- Knowledge of Full-Stack AI/ML Deployment (e.g. scalable ML pipelines(MLOps) using Docker, Kubernetes, FastAPI, cloud services, or other modern toolsets)
- Willingness to learn and continue developing knowledge in an up-and-coming field.
- Excellent problem-solving skills with the ability to thrive in a demanding, fast-paced work environment.
- Solid interpersonal and communication skills and a willingness to collaborate cross-functionally with different teams.