Senior AI Engineer - ML System Evaluation Engineering

Location: Mississauga, On, Canada

Description:

We seek a highly motivated Senior AI Engineer to join the Computational Sciences organization. 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 novel 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.