Ai à Canada

Integrated Resources, Inc (IRI) is recruiting a Senior AI Engineer to join the Computational Sciences organization in Client Research and Early Development (gRED). This role focuses on leveraging AI to accelerate drug discovery and target discovery efforts, including large-scale foundation models across biochemical modalities, multi-modal reasoning, and autonomous agent design for scientific discovery, drug development, and complex decision-making pipelines.

This role involves developing, deploying, evaluating, and scaling LLM-based agents across different modalities, with a focus on evaluation, benchmarking, scaling, model deployment, and MLOps. The successful candidate will work in a multidisciplinary environment alongside AI scientists, AI engineers, and computational biologists/chemists in a research-focused team. Prior biology/chemistry experience is not required.

• Design, optimize, evaluate and deploy cutting-edge deep learning models (e.g., large language models, multi-modal transformers) and data pipelines.
• Optimize and scale model and data pipelines for performance and accuracy.
• Monitor and maintain deployed models, ensuring strong performance in applications.
• Collaborate with cross-functional teams to translate Client ML methods into impactful applications for drug discovery and target discovery.
• Contribute to developing, deploying, evaluating and scaling LLM-based agents across modalities for complex decision-making pipelines.

• Hybrid role requiring presence on the Mississauga campus 2 times per week (as preferred by HM).
• Duration – 12+ months with possibility of extension.
• Base pay range: 69.00 / hr - 80.00 / hr (provided by IRI; actual pay based on skills and experience).
• Job function: Information Technology; Industries: Information Services, Biotechnology Research, and Pharmaceutical Manufacturing.

• Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
• Strong foundations in data structures, algorithms, and software engineering principles.
• Demonstrated experience in deep learning (e.g., prior projects or publications).
• Excellent Python and PyTorch programming skills.
• Demonstrated experience with MLOps, model deployment (e.g., Triton, ONNX), and API-based AI systems.
• Experience with large-scale distributed training and/or multi-GPU/cloud infrastructure (e.g., Ray, FSDP, DeepSpeed, TPU).
• Passionate about developing scalable, efficient, and well-documented software.
• Hands-on experience with LLMs (in-context strategies or fine-tuning) and agent-based systems is a plus.
• 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 ownership of challenges from start to finish and proactively acquire knowledge to drive solutions forward.