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 field4+ years of enterprise software product development experience, with a solid understanding of object-oriented design patterns, concurrency / multithreading, and scalable AI and GenAI model deploymentStrong programming skills in Python, PyTorch, TensorFlow, and related librariesProficiency in RegEx, Spacy, NLTK, and NLP techniques for text representation and semantic extractionHands-on experience in developing, training, and fine-tuning LLMs and AI modelsPractical understanding and experience in implementing techniques like CNN, RNN, GANs, RAG, Langchain, and TransformersExpertise in Prompt Engineering techniques and various vector databases
Familiarity with Cloud Computing Platforms like AWS / AzureExperience with Docker, Kubernetes, CI / CD pipelinesExcellent analytical and problem-solving skills. Strong communication skills and ability to collaborate effectively with cross-functional teamsSkills and Experience
Python, PyTorch, TensorFlow, and related libraries and modulesDeep learning, Computer Vision, CNN, RNN, LSTMRegular Expressions (RegEx), Spacy, NLTK, and NLP techniquesLarge Language Models (LLMs), Transformers, LSTMs, RNNs, and GANsConversational AI (Chatbots), Prompt EngineeringVector Databases (Pinecone, Cassandra, etc. ), Database TechnologiesCloud Computing Platforms (AWS, Azure, GCP)Desirable
Knowledge of various machine learning algorithms, reinforcement learning and Image ProcessingDeployment and Application Development Technologies like Flask, FastAPIData preprocessing libraries like NumPy, PandasFamiliarity with MySQL and NoSQL databasesSkills Required
Tensorflow, Pytorch, Gcp, Azure, Python, Aws