Sr Data Scientist-Innovation lab

Sr Data Scientist

Job Responsibilities:

• LLM Architecture: Good understanding of the architecture underlying large language models such as Transformer-based models and their variants. Design and implement deep learning model architectures using PyTorch.
  
• Language Model Training and Fine-Tuning: Experience in training large-scale language models from scratch as well as fine-tuning pre-trained models on domain data.
  
• Data Preprocessing for NLP: Skilled in preprocessing textual data including tokenization stemming lemmatization and handling of different text encoding.
  
• Transfer Learning and Adaptation: Proficiency in applying transfer learning techniques to adapt existing LLMs to new languages domains or specific business needs.
  
• Data Annotation and Evaluation: Skills in designing and implementing data annotation strategies for training LLMs and evaluating their performance using appropriate metrics.
  
• Scalability and Deployment: Experience in scaling LLMs for production environments ensuring efficiency and robustness in deployment.
  
• Model Training Optimization and Evaluation: Evaluate the performance of PyTorch models using appropriate metrics and techniques like cross-validation holdout sets or online evaluation. This encompasses the complete cycle of training fine-tuning and validating language models. You will be designing and adapting LLMs for use in virtual assistants Information retrieval and extraction etc.
  
• Experimentation with Emerging Technologies and Methods: Actively exploring new technologies and methodologies in language model development including experimental frameworks and software tools.
  
• LLM Alignment: Understanding of algorithms like DPO PPO KPO RLHF and using it for guardrails.
  
• AI Data Retrieval: Data retrieval from unstructured data extract key value pairs using techniques like donut layoutLM table transformers.
  
• Analyze data and build EDAs to identify data patterns Hands-on and strong understanding of concepts in Deep Learning and NLP Proficient in TensorFlow and similar libraries.
  

Required Qualifications

• 5 years of hands-on experience in developing and deploying Large Language Models and Machine learning and working with Pytorch.
  
• A thorough understanding of machine learning particularly deep learning techniques including knowledge of neural network architectures training methods and optimization algorithms.
  
• Proficiency in AI technology Python including experience with NLP libraries (e.g. Hugging Face Transformers NLTK spaCy) text classification.
  
• Experience with frameworks: PyTorch or Tensorflow.
  
• Experience with cloud services (AWS Azure) and ML deployment tool Docker
  
• Familiarity with model fine-tuning and optimization techniques for LLMs.
  
• Proven track record of innovative solutions in the field of LLMs.
  
• Strong communication skills with the ability to explain complex AI concepts to non-expert audiences.
  

Additional good to have qualifications:

• 4 years experience in data analytics data science quantitative analysis using statistical computer languages to draw insights from large data sets 3 years experience in Python development preferably delivering production code for data applications.
  
• Experience with unstructured data or computer vision models is a plus.
  
• Experience with SQL is a big plus Extensive model implementation experience using Scikit.
  
• Experience designing and developing for security critical applications; experience with the specifics for HIPAA/PHI/PII/GDPR a big plus.
  
• Basic experience with Linux Git Jupyter Notebooks is must Knowledge of Agile development practices Flexibility and adaptability to respond to a rapidly changing environment.
  
• Experience with distributed computational techniques and job orchestration tools and platforms is very valuable: airflow etc.