Machine Learning Research Scientist | GenerativeModels | Protein Design | Deep Learning | Python | Hybrid, LDN Weare looking for multiple highly skilled machine learningresearchers with strong expertise in generative modeling is soughtto join an interdisciplinary team of machine learning experts,protein engineers, and biologists. The team collaborates totransform how biology is controlled and diseases are cured. Therole involves architecting innovative generative models aimed atdesigning new proteins that demonstrate functionality in wet labassays.This company specializes in developing generative AI modelsfor synthetic biology, focusing on designing and reprogrammingbiological systems, including gene editing technologies to enabletreatments for complex genetic diseases. Operating at theintersection of AI and biology, the team is driven by innovation,curiosity, and a commitment to creating significant positive globalimpact.RequirementsExpertise in generative modeling: The idealcandidate has a proven track record in machine learning, withexperience leading or contributing to high-profile projects, asevidenced by widely used open-source libraries, major productlaunches, or impactful publications (e.g., NeurIPS, ICML, ICLR, orNature).Skilled in ML development: They write robust, maintainableML code, have proficiency in version control and code reviewsystems, and are capable of producing high-quality prototypes andproduction code. They have experience running models on cloudhardware and parallelizing data and models across accelerators.Dataengineering capabilities: The candidate is experienced in buildingML data pipelines for training and evaluating deep learning models,including raw data analysis, dataset management, and scalablepipeline construction.Passion for optimization: They possessin-depth knowledge of ML libraries, hardware interactions, andoptimization techniques for model training, inference speed, andvalidation metrics performance.Mission-driven and curious:Motivated by the opportunity to make a positive global impact, theyapproach problems with relentless curiosity andadaptability.Adaptability in dynamic environments: They thrive infast-paced settings, achieving goals efficiently andeffectively.Desired QualificationsExperience in computationalbiology or protein design: Experience with ML-driven projects inbiology is advantageous.Natural science background: Academictraining in fields like physics, biology, or chemistry is aplus.Key responsibilitiesDevelop machine learning models withreal-world applications (~90%):Curate and manage training andevaluation data.Design and implement ML evaluation metrics alignedwith organizational goals.Rapidly prototype generative models andperform detailed analyses of their performance.Collaborate withresearchers, engineers, and designers, maintaining a high-qualitycodebase.Support the maintenance of compute and MLinfrastructure.Coordinate with biology teams for wet lab testingcampaigns and conduct model inferences for biological targettesting.Incorporate feedback from wet lab results to refine andimprove models.Engage in self-development (~10%):Stay updated onthe latest ML research and advancements.Develop a strongunderstanding of protein and cell biology.Share knowledge byorganizing and presenting in reading groups or at conferences.Excellent compensation - six figures+ & equity Hybrid Working –3 days p/w onsite. Central London Permanent positionIf you areinterested in finding out more about this hire please reach out for immediate consideration.Machine LearningResearch Scientist | Generative Models | Protein Design | DeepLearning | Python | Hybrid, LDN
