Associate Director, AI
On-siteBengaluru, Karnataka, India
Job Summary
Design and deploy machine learning models for large-scale analysis of clinical transcriptomics data to predict clinical events, segment patients, or screen compounds. Collaborate with scientists across pre-clinical and clinical stages to build platforms underpinning research, applying novel data science methodologies where off-the-shelf solutions fail. Manage relationships with stakeholders to communicate results, uncertainties, and limitations while ensuring production-grade infrastructure scales exploratory work. Work across European, Asian, and Chinese timezones to evaluate AI solutions and maintain secure computing environments aligned with cybersecurity and data privacy standards.
Required Qualifications
- PhD (or equivalent years of experience) in mathematics, computer science, engineering, physics, statistics, computational sciences or a related field
- Proven experience in applying AI and machine learning to solve problems in commercial context
- Demonstrated experience in implementing machine learning/AI workflows to automate bioinformatics analysis pipelines, ideally in the Pharma and/or Healthcare space
- Familiarity with modern foundation models for biological data (e.g., transcriptomics or Cell Painting)
- Experience of manipulating and analysing large high dimensionality unstructured datasets, drawing conclusions, defining recommended actions, and reporting results across stakeholders
- Advanced skills in programming languages such as Python, and experience with AI libraries and frameworks (e.g., TensorFlow, PyTorch)
- Strong knowledge of software development and machine learning deployment principles
- Demonstratable experience working with AWS or a similar cloud environment
- Experience working in a team with ML engineers and/or software developers
- Familiarity with GitHub, CI/CD pipeline, and best DevOps and MLOps practices
- Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical partners
- Strong leadership and project management skills, with a track record of leading successful bioinformatics projects
- Knowledge of AI ethics and responsible AI practices
Desired Qualifications
- Experience building ML/AI models to predict compound safety
- Experience in life sciences, healthcare, or pharmaceutical industry
- Familiarity with existing machine vision models: CNNs, vision transformers, diffusion models etc. for self-supervised and multimodal training (e.g., ResNet, UNet, DINO, CLIP, Stable Diffusion)
- Experience working with proteomics datasets
- Experience in a complex global organization
- Experience working in an Agile team with knowledge or experience of working in product or platform-focused delivery
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.