Data Scientist, Machine Learning Operations

DATA SCIENTIST / MACHINE LEARNING:
Machine Learning Expertise: Hands-on experience with ML frameworks
NLP Knowledge: Strong understanding of natural language processing, embeddings, and transformer-based models (e.g., BERT, RoBERTa, GPT).
Vector Search Tools: Proficiency in tools like FAISS, Milvus, Pinecone, or other ANN libraries.
Search Algorithms: In-depth knowledge of similarity search techniques, including cosine similarity, dot-product scoring, and clustering methods.
Programming Skills: Strong coding abilities in Python (experience with libraries like NumPy, Pandas, Scikit-learn, Hugging Face Transformers, etc.).
Cloud/DevOps Knowledge: Familiarity with cloud platforms (Azure) and containerization/orchestration tools like Docker and Kubernetes.
Awareness of latest AI trends (GenAI, Agentic AI) .
Docker Error analysis for SW and ML algorithms.
Data-centric mindset to do EDAs, curate data Business acumen
Practical experience with text and image processing. Computer Vision, NLP, LLMs, VLMs
Good command of version control and python programming (esp. related to ML and data science)