ML Research Engineer

May 21

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Causaly

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Causaly accelerates how humans acquire knowledge and develop insights in Biomedicine.

Artificial Intelligence • Natural Language Understanding • Knowledge graphs • Pharma • Life Sciences

51 - 200

💰 Venture Round on 2022-10

Description

• The ML Research Engineer will be a key addition to Causaly’s AI organisation. You will work alongside an interdisciplinary team of experts to develop and implement novel solutions to complex challenges with high levels of uncertainty. • Fine-tune and optimize large language models for specific tasks within biomedical research and drug discovery • Design and implement intelligent agents capable of generating and testing scientific hypotheses, as well as interacting with the Causaly platform and external data sources • Design and implement reinforcement learning algorithms to automate various aspects of drug discovery, including target identification and lead optimization • Design, develop and maintain model training, evaluation, monitoring, dataset annotation and dataset management infrastructure • Adopt an agile approach with quick iterations and adaptable solutions to meet the evolving needs of our product • Document development milestones for a hybrid and multidisciplinary team • Work closely with scientists to design large scale experiments to mature and productionize ML capabilities

Requirements

• MSc/PhD in computer science, machine learning or equivalent • Strong analytical and proven problem-solving skills • Demonstrable industry experience delivering AI/ML frameworks for a product • Expertise in working with ML frameworks such as PyTorch, Tensorflow, scikit-learn, Langchain • Experience with DL architectures such as transformers/CNNs • Excellent programming skills in Python and object-oriented paradigm • Agile software development experience (comfortable with development management tools such as Jira, Rally) • Excellent written and verbal communication skills Nice-to-Have Skills and Background • Applied RAG experience in industry • Experience in Biomedical data or computational sciences • Experience in building Reinforcement Learning frameworks • Experience in cloud platforms such as GCP or AWS • Experience with MLOps/LLMOps frameworks and best practices

Benefits

• Competitive compensation package • Private medical insurance (underwritten on a medical health disregarded basis) • Life insurance (4 x salary) • Individual training/development budget through Learnerbly • Individual wellbeing budget through Juno • 25 days holiday plus public holidays and 1 day birthday leave per year • Hybrid working (home + office) • Potential to have real impact and accelerated career growth as an early member of a multinational team that's building a transformative knowledge product