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Senior Machine Learning Engineer
3 weeks ago
Job Title: Senior Machine Learning Engineer
About Insilico
Insilico Medicine is an end-to-end, artificial intelligence (AI) -driven pharma- biotechnology company with a mission to accelerate drug discovery and development by leveraging our rapidly evolving, proprietary platform across biology, chemistry, and clinical development.
For more info, visit our website
About Role
Insilico Medicine seeks a Senior Machine Learning Engineer for the Chemistry42 product a comprehensive small-molecule drug discovery platform.
Place of work
3710-1250 René-Lévesque West Boulevard, Montréal, QC-H3B 4W8, Canada
Reports to
ML team leader
Responsibilities
- Conduct ideation, research, and development of state-of-the-art AI-driven systems for small molecule design.
- Spearhead initiatives to advance and refine our suite of AI tools for small molecule generation, screening, simulation, and prediction.
- Architect and engineer AI-powered feature prototypes for the Chemistry42 platform, enhancing product discovery and user growth.
- Champion the optimization and support of critical AI components within the platform, ensuring scalability, efficiency, and effectiveness.
Requirements
Education
Ph.D. or M.S. in Computer Science, Artificial Intelligence, Data Science, Computational Chemistry, Medicinal Chemistry, or closely related fields
Experience and Required Skills
- At least five years of experience in ML engineering and Python
- At least two years in a senior/lead position
- Extensive experience and a strong background in AI/ML/DL: transformers, GNNs, diffusion models, RNNs, CNNs, GANs, VAEs, flow-based generative models, reinforcement learning, evolutionary algorithms
- Be experienced in Pytorch, Numpy, Pandas, Scikit-Learn, LangChain, JupyterLab, Plotly, Git, AWS, W&B
- An ability to quickly test hypotheses with prototypes for product R&D
- Ability to work under pressure with tight deadlines
- Motivation to learn new things fast and improve the product with AI solutions
Desirable Skills
- Background in chemistry or chemoinformatics
- Successful experience in ML competitions (Kaggle, etc.)
- Proven track of publications in machine learning for drug discovery
- Skills and mindset for feature/component/product ownership
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