Senior AI Engineer

Griffin Fire
London
1 month ago
Applications closed

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Machine Learning Engineer, London

Lead / Senior Software Engineer - ML/AI

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 worlds 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:

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

Minimum Qualifications:

  1. MSc/PhD in computer science, machine learning or equivalent.
  2. Strong analytical and proven problem-solving skills.
  3. Experience fine-tuning LLMs for NLP tasks in industry.
  4. Demonstrable industry experience delivering AI/ML frameworks for a product.
  5. Expertise in working with ML frameworks such as PyTorch, Tensorflow, scikit-learn, Langchain.
  6. Experience with DL architectures such as transformers/CNNs.
  7. Excellent programming skills in Python and object-oriented paradigm.
  8. Agile software development experience.

Preferred Qualifications:

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

Benefits:

  1. Competitive compensation package.
  2. Private medical insurance (underwritten on a medical health disregarded basis).
  3. Life insurance (4 x salary).
  4. Individual training/development budget through Learnerbly.
  5. Individual wellbeing budget through Juno.
  6. 25 days holiday plus public holidays and 1 day birthday leave per year.
  7. Hybrid working (home + office).
  8. Potential to have real impact and accelerated career growth as an early member of a multinational team thats building a transformative knowledge product.

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

Diversity. Equity. Inclusion. They are more than words at Causaly. Its how we work together. Its how we build teams. Its how we grow leaders. Its what we nurture and celebrate. Its what helps us innovate. Its 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.

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