BenevolentAI is seeking to hire a talented Machine Learning Engineer to contribute to the development of our industry-leading AI models. At BenevolentAI, we harness the power of artificial intelligence (AI) and human expertise to revolutionise the field of drug discovery. Our unique computational R&D platform, combined with our in-house pipeline of drug programmes, enables us to develop new and more effective medicines. With offices in London and a state-of-the-art research facility in Cambridge (UK), we have cultivated a diverse team of professionals from various scientific, technological, and business backgrounds. Our team is united by a shared passion for making a meaningful impact on healthcare through innovation and collaboration.
The Advanced Machine Learning Engineer is a key role which will contribute to model productionisation, data engineering, and accelerating model development. You will work closely with the Lead Machine Learning Engineering and be a member of a multidisciplinary team of AI Scientists, Software Engineers, Informaticians and Drug Discoverers.
Responsibilities
- You will productionise models across Product and Tech that support a range of drug discovery and development phases including target identification and chemistry.
- You will speed up model development by simplifying, orchestrating, automating or distributing workflows.
- You will work in collaboration with users from different disciplines, providing them with regular updates and incorporating their feedback into your products.
- You will share knowledge and results of your work, promote best practice and onboard users.
- You will ensure that engineering is of the highest quality, that we track experiments and our models are reproducible.
- You will collaborate with AI scientists and contribute to new model development ideas.
- You will develop tools and workflows using Airflow, Kubernetes, Spark, PyTorch and more.
We are looking for
- An inherent interest in drug-discovery with a team player mindset.
- An MSc or PhD in computer science, machine learning, or a related discipline.
- Good Python coding skills.
- Experience working with PyTorch, Tensorflow, jax or other deep learning frameworks.
- Experience with AWS/GCP.
- Knowledge of machine learning and deep learning fundamentals.
- Experience with model training in GPUs and orchestration of data/modelling pipelines.
- Experience working with kubernetes, Spark, Weights and Biases, Sagemaker (or other model serving frameworks) and/or large scale biomedical datasets would be pluses.
