About the role:

As a Data Science Engineer, become a part of a cross-functional development team who is working with a leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, our client serves 1500+ Enterprise customers globally and has grown to 2, 500 talented leaders, data scientists, and other professionals across over 20 countries.

Responsibilities

Collaborate with engineers, data scientists, and business analysts to understand requirements, refine models, and integrate LLMs into AI solutions
Development and implementation of Deep learning algorithms for AI solutions
Stay updated with recent trends in GENAI and apply the latest research and techniques to projects
Collaborate with clients to understand their business challenges and tailor GENAI solutions that provide strategic advantages
Preprocess raw data, including text normalization, tokenization, and other techniques, to make it suitable for use with NLP models
Setup and train large language models (BERT, GPT-3, etc. ) and other state-of-the-art neural networks
Conduct thorough testing and validation to ensure accuracy and reliability of model implementations
Perform statistical analysis of results and optimize model performance for various computational environments, including cloud and edge computing platforms

Requirements

Bachelors/Master s degree in computer science, engineering, or a related field
4+ years of enterprise software product development experience, with a solid understanding of object-oriented design patterns, concurrency/multithreading, and scalable AI and GenAI model deployment
Strong programming skills in Python, PyTorch, TensorFlow, and related libraries
Proficiency in RegEx, Spacy, NLTK, and NLP techniques for text representation and semantic extraction
Hands-on experience in developing, training, and fine-tuning LLMs and AI models
Practical understanding and experience in implementing techniques like CNN, RNN, GANs, RAG, Langchain, and Transformers

Expertise in Prompt Engineering techniques and various vector databases

Familiarity with Cloud Computing Platforms like AWS/Azure
Experience with Docker, Kubernetes, CI/CD pipelines
Excellent analytical and problem-solving skills. Strong communication skills and ability to collaborate effectively with cross-functional teams

Skills and Experience

Python, PyTorch, TensorFlow, and related libraries and modules
Deep learning, Computer Vision, CNN, RNN, LSTM
Regular Expressions (RegEx), Spacy, NLTK, and NLP techniques
Large Language Models (LLMs), Transformers, LSTMs, RNNs, and GANs
Conversational AI (Chatbots), Prompt Engineering
Vector Databases (Pinecone, Cassandra, etc. ), Database Technologies
Cloud Computing Platforms (AWS, Azure, GCP)

Desirable

Knowledge of various machine learning algorithms, reinforcement learning and Image Processing
Deployment and Application Development Technologies like Flask, FastAPI
Data preprocessing libraries like NumPy, Pandas
Familiarity with MySQL and NoSQL databases

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