PSSM ML/AI Engineer

Pharmaceutical Sciences Small Molecules (PSSM) develops the APIs, formulations & manufacturing processes needed to transform laboratory candidates into potential new drugs.  Simply put, PSSM is Making Today’s Discoveries Tomorrow’s Medicines. 

We are seeking a ML/AI engineer to join the newly formed Data Sciences organization within PSSM in Chennai, India. In this role the successful candidate will play a crucial part in supporting PSSM digital evolution by harnessing the power of ML/AI technology and developing PSSM applications.  The candidate will leverage your expertise in ML and DL algorithms, coding, and MLOps to unlock ML velocity, governance, and production readiness that accelerates execution of organization strategic imperatives.  Candidates should possess a deep understanding of various machine learning algorithms with hands-on experience for the entire lifecycle of ML projects, from designing and building models to deploying and monitoring them in production.  This role will collaborate with colleagues across all of PSSM, Pfizer Digital and our partner organizations to develop and implement ML/AI solutions to PSSM business workflows and knowledge systems.

The Pfizer AI/ML ecosystem is in a rapid growth phase, and we anticipate the selected candidate will be part of enhancing the impact of AI/ML within Pfizer, both by direct application to the portfolio, but also through technology and tool development. This may include advancing new technology for process automation, machine learning, generative AI application, and information system, amongst others. This is a tremendous opportunity for someone interested in continuous development of their skills in these and related areas.

ROLE RESPONSIBILITIES

1. Collaborate with partner development lines and data science team members to comprehend PSSM business needs and translate them into technical requirements for applying machine learning solutions.
2. Preprocess and clean large PharmSci datasets for model training and evaluation, ensuring data quality and addressing potential biases.
3. Design, develop, and implement machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) to PSSM business workflows.
4. Incorporating MLOps tools and best practices to support the integration of ML models into production systems, monitor and maintain models, ensuring high availability and performance.
5. Continuously improve machine learning pipelines by automating tasks and optimizing workflows.
6. Document machine learning projects and technical decisions clearly and concisely. Communicate results with stakeholders to enhance business decisions and/or influence strategic direction.
7. Stay abreast with advancements in machine learning research for diverse environments (cloud and edge). Identify opportunities for enhanced performance and innovation.
8. Support upskilling the organization on the application of ML/ AI and to help build a continuous learning culture.