Senior AI Engineer - ML System Evaluation Engineering

Description:
We seek a highly motivated Senior AI Engineer to join the Computational Sciences organization in Client Research and Early Development (gRED).
Our group is dedicated to leveraging AI to accelerate drug discovery and target discovery efforts. Our focus spans large-scale foundation models across biochemical modalities, multi-modal reasoning, and autonomous agent design, with a strong emphasis on scientific discovery, drug development, and complex decision-making pipelines.

The successful candidate will have a strong background in software development, a passion for quality and scalability, and an interest in creating evaluation systems. You will contribute to developing, deploying, evaluating and scaling LLM based agents across different modalities for complex decision-making pipelines. You will work at the intersection of deep learning and large-scale optimization, with a focus on evaluation, benchmarking, scaling, model deployment, and MLOps. The successful candidate will work in an exciting and multidisciplinary environment alongside AI scientists, AI engineers, and computational biologists/chemists in a research-focused team. Prior experience in biology/chemistry is not required for this role.

The role
Design, optimize, evaluate and deploy cutting-edge deep learning models (e.g. large language models, multi-modal transformers, etc.) and data pipelines.
Optimize and scale model and data pipelines for performance and accuracy.
Monitor and maintain deployed models, ensuring the best performance in applications.
Collaborate with cross-functional teams to translate Client ML methods into impactful applications for drug discovery and target discovery.

Who you are
Master's degree in Computer Science, Machine Learning, Data Science, or a related field .
Technical skills:
o Strong foundations in data structures, algorithms, and software engineering principles.
o Demonstrated experience in deep learning (e.g., previous projects or publications).
o Excellent Python and PyTorch programming skills.
o Demonstrated experience with MLOps, model deployment (e.g., Triton, ONNX), and API-based AI systems.
o Experience with large-scale distributed training and/or multi-GPU/cloud infrastructure (e.g., Ray, FSDP, DeepSpeed, TPU).
o Passionate about developing scalable, efficient, and well-documented software.
o Hands-on experience with LLMs (e.g., in-context strategies or finetuning) and agent-based systems is a plus.
o Prior experience in drug discovery and biomedical AI is not required but is a plus.
Strong communication and collaboration skills with the ability to effectively communicate technical concepts to both technical and non-technical audiences.
Take full ownership of challenges from start to finish and proactively acquire any necessary knowledge to drive solutions forward.