Machine Learning Engineer

About us 

Founded in 2018, Causaly accelerates how humans acquire knowledge and develop insights in Biomedicine. Our production-grade generative AI platform for research insights and knowledge automation enables thousands of scientists to discover evidence from millions of academic publications, clinical trials, regulatory documents, patents and other data sources… in minutes. 

We work with some of the world's largest biopharma companies and institutions on use cases spanning Drug Discovery, Safety and Competitive Intelligence. You can read more about how we accelerate knowledge acquisition and improve decision making in our blog posts here: Blog - Causaly 

We are backed by top VCs including ICONIQ, Index Ventures, Pentech and Marathon. 

About the role: 

The ML Engineer will be a key addition to Causaly’s AI organisation. You will work alongside an interdisciplinary team of experts to build scalable and robust solutions to highly complex NLP problems that drive business impact. You will develop and implement cutting-edge machine learning algorithms to help us extract valuable insights from large biomedical datasets. Please note we are unable to sponsor visas for this position.

Responsibilities:

• Lead the development and optimization of machine learning models and algorithms for processing and extracting insights from scientific literature
• Collaborate with Research Engineers to experiment with new ideas, evaluate models, and improve performance
• Work with the engineering team to ensure seamless integration of machine learning models into Causaly's platform, ensuring accuracy, efficiency, and scalability.
• Participate in code reviews and ensure high-quality standards for all deliverables.
• Stay up-to-date with the latest research and advancements in machine learning and related fields.

• 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

Preferred Qualifications

• Experience fine-tuning LLMs for NLP tasks in industry

• Experience in Biomedical data or computational sciences 
• Experience in cloud platforms such as GCP or AWS 
• Experience with MLOps/LLMOps frameworks and best practices