5+ years of production model deployment experience for ML solutions Highly motivated/self-starter with a sense of ownership, willingness to learn, and desire to succeed. Strong teamwork, problem-solving, and analytical skills Deep knowledge of math, probability, statistics, and algorithms Strong understanding of Pharma Quality Standards and Practices Excellent leadership and interpersonal skills (both verbal and written)
Required /Proven experience with the following:
Designing, developing, and researching Machine Learning systems, models, and schemes through data science and data analytics prototypes. Understanding of Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG) Develop and implement technical efforts to design, build, and deploy AWS ML models at the direction of lead architects, including large-scale data processing, computationally intensive statistical modelling, and advanced analytics. Familiarity with deep learning, machine learning and NLP/NLG frameworks (like Keras, TensorFlow or PyTorch etc.), HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.) Should have experience in AWS services such as SageMaker, Elasticsearch, and general knowledge of AWS architecture & other services. Ability to write robust code in Python, Java and R Experience optimizing model hyperparameter tuning for speed and cost. Experience in building MLOps pipeline using MLOps frameworks like Kubeflow, MLFlow, and Data Robot Experience with Docker and Kubernetes Familiarity with Event bridge and AWS step function for workload orchestration Experience with Agile Development.