About us:

Founded in 2018, Causaly accelerates how humans acquire knowledge and develop insights in Biomedicine. We enable researchers and decision-makers to discover evidence from millions of academic publications, clinical trials, regulatory documents, patents and other data sources… in minutes.

Using our AI technology, we are developing the world’s biggest knowledge platform in Biomedicine powered by a high-precision Knowledge Graph.

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 Index Ventures, Pentech and Marathon.

About the role:

The ML Research Engineer will be a technical addition to Causaly’s Data and ML team to build the production-level AI Engine of the Causaly Platform. You will work in an interdisciplinary team of data scientists, software engineers, biologists and automation engineers to build data and decision pipelines that support drug discovery.

Responsibilities

• Follow the LLM literature and implement state-of-the-art algorithms to build information extraction and integration capabilities that form the core components of our product offering.
• Design, develop and maintain NLP pipelines to complement human decisions via supporting facts and evidence.
• Design, develop and maintain model training, evaluation, monitoring, dataset annotation and dataset management infrastructure
• Adopt a test-driven approach to produce a high-quality and efficient codebase, perform code reviews with other ML engineers to accept stories/deliverables
• Adopt an agile approach with quick iterations and adaptable solutions to meet the evolving needs of the 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

• MS in computer science or equivalent
• Strong analytical and problem solving skills, hands-on model development experience
• 5+ years of experience delivering AI/ML frameworks for a product
• Expertise in working with ML frameworks such as PyTorch, Tensorflow, scikit-learn, langchain
• 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

• MS/PhD in data science, NLP or equivalent
• Experience with DL architectures such as transformers/CNNs
• Experience in building Reinforcement Learning frameworks
• Experience in cloud platforms such as GCP or AWS

• 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

Be yourself at Causaly... Difference is valued. Everyone belongs.

Diversity. Equity. Inclusion. They are more than words at Causaly. It's how we work together. It's how we build teams. It's how we grow leaders. It's what we nurture and celebrate. It's what helps us innovate. It's what helps us connect with the customers and communities we serve.

We are on a mission to accelerate scientific breakthroughs for ALL humankind and we are proud to be an equal opportunity employer. We welcome applications from all backgrounds and fairly consider qualified candidates without regard to race, ethnic or national origin, gender, gender identity or expression, sexual orientation, disability, neurodiversity, genetics, age, religion or belief, marital/civil partnership status, domestic / family status, veteran status or any other difference.