Data Scientist - NLP/Machine Learning (3-10 yrs)

Job Responsibilities :

- Bachelor's Degree/Masters/PHD in Computer Science with specialization in Data Science

- Experience in Computer Vision experience and exposure to developing document processing

- Experience in solutions and extracting several business entities from documents with unstructured layouts

- Design, architect and develop AI products end to end from inception to operationalization based on Computer Vision and NLP

- Experience or knowledge on Prompt Engineering Quick learner who can tackle new problems and map them to leverage the latest advancements in technology. Technical awareness to recent developments in Computer Vision e.g. YOLO, R-CNN and NLP e.g.

- Transformer Models and ability to build products based on new models like Layout LM and GenAI

- Experience with Open Source LLM and Langchain Framework and and designing efficient prompt for LLMs.

- Proven ability with NLP and text-based extraction techniques.

- Experience in Generative AI technologies, such as diffusion and/or language models.

- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

- Familiarity with cloud computing platforms such as GCP or AWS. - Experience to deploy and monitor model in cloud environment.

- Experience with common data science toolkits, such as NumPy, Pandas etc

- Proficiency in using query languages such as SQL

- Good applied statistics skills, such as distributions, statistical testing, regression, etc.

- Experience working with large data sets along with data modeling, language development, and database technologies

Knowledge Technical :

- Self-Motivated, Dynamic & result oriented Professional with experience in Microsoft Azure and AWS Zero/One/Few shot) learning, fine-tuning, RAG.

- Good to have patents or research papers in ML/AI or Should have patents or research papers in ML/AI

- Expertise in applying a broad variety of ML methods including NLP and LLM to solve business problems using large amounts of data

- Proficiency in programming languages such as Python, R, or SQL.

- Experience with big data platforms and tools (e.g., Hadoop, Spark).

- Strong understanding of cloud-based data solutions (e.g., AWS, Azure, Google Cloud).