Description

You will develop and optimize AI models, conduct experiments to evaluate their performance, and collaborate with scientists to tackle technical challenges while ensuring smooth integration into production.

Requirements

• •PhD in technical subject with engineering focus
• •BSc, MSc and 2+ years ML experience
• •Strong general engineering experience
• •Software design and algorithms expertise
• •Experience with modern ML frameworks
• •Knowledge of distributed systems
• •Experience with compilers like XLA
• •Experience in large scale model training
• •Experience navigating complex research codebases
• •Knowledge of databases and data processing
• •Strong understanding of numerical methods
• •Strong fundamentals in mathematics
• •Experience with ML research lifecycle
• •Strong understanding of ML theory
• •Strong understanding of data structures
• •Interest in chemistry and biology
• •Experience with biomedical data
• •Knowledge of pharmaceutical industry

Tasks

• •Translate research concepts into practical AI implementations.
• •Develop and optimize state-of-the-art AI models.
• •Build and maintain robust codebases and data pipelines.
• •Design and run experiments to evaluate ML model performance.
• •Tune and maintain AI/ML models, including data preparation.
• •Implement algorithms to analyze AI model performance.
• •Optimize performance of AI/ML models like Diffusion models and Transformers.
• •Advise on production integration of AI/ML models.
• •Develop specialized tools and infrastructure for AI tasks.
• •Collaborate with research scientists and engineers in discussions.
• •Participate in code reviews to foster collaboration.
• •Identify and address technical challenges proactively.
• •Stay updated on AI advancements and develop scalable solutions.
• •Execute independent engineering projects towards research goals.

Tools & Technologies