Senior Expert (AI Engineering)

Role Overview: As a Senior Expert in AI-Engineering at Novartis, you will play a crucial role in designing and training advanced machine learning models for drug discovery. You will be at the forefront of innovation, transforming cutting-edge AI concepts into scalable solutions that accelerate the process of discovering breakthrough medicines. Collaborating with leading scientists and AI experts, you will drive the translation of pioneering research into impactful tools, ensuring reproducibility, efficiency, and readiness to tackle complex biomedical challenges. This position offers you the opportunity to directly influence how modern AI reshapes scientific discovery and enhances patient outcomes. Key Responsibilities: - Design and train advanced machine learning models for drug discovery, including deep learning and graph-based architectures. - Own the end-to-end model lifecycle from problem definition to production deployment and continuous improvement. - Conduct rigorous benchmarking, validation, and performance evaluation against scientific and business objectives. - Deploy scalable, reliable model inference services meeting latency, throughput, and cost requirements. - Build automated training, retraining, and monitoring pipelines, including model drift detection mechanisms. - Optimize models and pipelines for performance, reliability, and scalability across production environments. - Establish and promote engineering best practices for reproducibility, testing, and deployment standards. - Collaborate with cross-functional teams to translate research innovations into production-ready AI solutions. - Partner with scientific experts to validate models against biological and chemical benchmarks. - Mentor teams and contribute to raising engineering excellence across the AI for Research organization. Qualifications Required: - Minimum four years of experience building, training, and deploying machine learning models with measurable real-world impact. - Deep proficiency in Python and frameworks such as PyTorch or JAX; expertise in model design and optimization. - Proven experience fine-tuning and deploying large pre-trained and foundation models, including language and scientific models. - Strong understanding of model evaluation, including benchmarking, cross-validation, and performance across data distributions. - Experience with distributed training and large-scale computing environments for high-performance model training. - Hands-on expertise optimizing models and pipelines for latency, throughput, cost, and production performance. - Experience with MLOps practices, including experiment tracking, model versioning, reproducibility, and cloud deployment. - Strong problem-solving, collaboration, and communication skills with the ability to drive engineering excellence in complex environments. Additional Details: Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities served. The company is dedicated to working with and providing reasonable accommodation to individuals with disabilities. If you require accommodation during the recruitment process or while performing essential job functions, please reach out to diversityandincl.india@novartis.com with details of your request and contact information. (Note: Skills Desired and other non-essential details have been omitted from the Job Description as per the provided instructions) Role Overview: As a Senior Expert in AI-Engineering at Novartis, you will play a crucial role in designing and training advanced machine learning models for drug discovery. You will be at the forefront of innovation, transforming cutting-edge AI concepts into scalable solutions that accelerate the process of discovering breakthrough medicines. Collaborating with leading scientists and AI experts, you will drive the translation of pioneering research into impactful tools, ensuring reproducibility, efficiency, and readiness to tackle complex biomedical challenges. This position offers you the opportunity to directly influence how modern AI reshapes scientific discovery and enhances patient outcomes. Key Responsibilities: - Design and train advanced machine learning models for drug discovery, including deep learning and graph-based architectures. - Own the end-to-end model lifecycle from problem definition to production deployment and continuous improvement. - Conduct rigorous benchmarking, validation, and performance evaluation against scientific and business objectives. - Deploy scalable, reliable model inference services meeting latency, throughput, and cost requirements. - Build automated training, retraining, and monitoring pipelines, including model drift detection mechanisms. - Optimize models and pipelines for performance, reliability, and scalability across production environments. - Establish and promote engineering best practices for reproducibility, testing, and deployment standards. -