Objectives of the role:

o Work in tandem with our engineering partners to identify and implement the

most optimal cloud-based ML solutions for the company

o Research, design and adopt cutting-edge NLG algorithms to address real-

world challenges such as summarisation.

o Define and document best practices and strategies regarding deployment

and infrastructure maintenance

o Ensure ML Model performance, uptime, and scale, maintaining high

standards of code quality and thoughtful design

o Maintain a platform that automates creating, training, deploying and

updating machine learning models.

o Managing BI Platforms in accordance with company security guidelines

o Build effective relationships with business areas, strategic vendors, and key

delivery partners such as the Advanced Analytics and Data Sciences

(AADS) group to share expertise and seek opportunities to reuse internal

processes and services, so we can streamline implementation and support

of key systems.

Required /Proven experience with the following:

o Designing, developing, and researching Machine Learning systems,

models, and schemes through data science and data analytics prototypes.

o Understanding of Natural Language Processing(NLP), Natural Language

Understanding(NLU) and Natural Language Generation(NLG)

o 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 modeling, and advanced analytics o 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.)

o Should have experience in AWS services such as SageMaker, Elasticsearch, and general knowledge of AWS architecture & other services

o Ability to write robust code in Python, Java and R

o Experience optimizing model hyperparameter tuning for speed and cost

o Experience in building MLOps pipeline using MLOps frameworks like Kubeflow, MLFlow, and DataRobot

o Experience with Docker and Kubernetes

o Familiarity with Eventbridge and AWS step function for workload orchestration

o Experience with Agile Development.

o Good experience in process improvement/change management methods

o Knowledge of various aspects of an enterprise technology architecture like business, information, data, network, and security

o Understanding and knowledge of system development life cycle methodologies (such as waterfall, agile software development, rapid prototyping, and DevOps)

o Understanding and knowledge of IT service management (ITSM) and Information Technology Infrastructure Library (ITIL)

o Excellent analytical, planning, organizational and technical and skills

o Skilled at influencing, guiding, and facilitating stakeholders and peers with decision making

o Ability to articulate new ideas and concepts to technical and nontechnical audiences

o Ability to understand the long-term ("big picture") and short-term perspectives of situations

Desirable Skills:

o 8-16 years of production model deployment experience for ML solutions

o Highly motivated/self-starter with a sense of ownership, willingness to learn, and desire to succeed

o Strong teamwork, problem-solving, and analytical skills

o Deep knowledge of math, probability, statistics and algorithms

o Strong understanding of Pharma Quality Standards and Practices

o Excellent leadership and interpersonal skills (both verbal and written)