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Jobs(38,923)/Machine Learning Engineer Role(464)/groundtruthlabs (1) - Machine Learning Scientist
groundtruthlabs

groundtruthlabs - Machine Learning Scientist

Remote - UK2w ago
RemoteEMEAArtificial IntelligenceData AnalyticsMachine Learning EngineerPythonLearning & Development

Requirements

• PhD or equivalent practical experience in a technical field • Experience and a track record of innovation in deep learning and statistical analyses • Expertise in processing and analysing large image datasets using statistical methods • Ability to work independently and as part of multidisciplinary team within in a fast-paced startup environment • Strong communication and collaboration skills. Both remote (excellent written communication is key) and in-person • Strong programming skills in Python and experience with PyTorch • Track record in computational pathology and/or single-cell transcriptomics analysis, sequencing • Clinical background or knowledge of cancer biology • Expertise in multimodality integration which includes histology data, clinical data, sequencing or other multi-omics • Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases • This is an opportunity to join a small, high-calibre team and take ownership of foundational engineering work at a pivotal stage of company growth. • You will work alongside talented machine learning scientists and engineers to build the platform that supports our research, partner delivery, and future products. The role is especially well suited to someone who enjoys building from the ground up, moving quickly, and having tangible impact across an organisation and field. • WORKING ENVIRONMENT • We primarily work remotely with a strong emphasis on efficient processes that enable high-quality work across asynchronous teams. At the same time, we recognise the importance of spending time together in person to share knowledge, solve hard problems, and build strong working relationships. We therefore expect this role to involve regular travel to London and Oxford. Indicatively, a typical month may involve 2-8 in-person days. • As a team, we value: • 1. Concise and engaged communication - we communicate clearly to work effectively in a remote setting. • 2. Pride in high-quality work - we pay attention to detail and deliver to the highest standard. • 3. A strategic approach - we think critically and creatively about complex issues. We identify the underlying patterns and leverage them to develop effective strategies • 4. Collaborative co-creation - we are open to diverse perspectives, bounce ideas off of each other, and build upon each other's strengths. • We welcome applications from all of society. We are committed to equal employment opportunity regardless of age; disability; gender reassignment; marriage and civil partnership; pregnancy and parental; race; religion or belief; sex; sexual orientation or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. • This is an opportunity to join a rapidly growing startup in the AI space and make a real impact in the field of blood cancer. • We are looking for software engineers who are thoughtful, rigorous, and committed to building reliable systems that matter. If you care about quality, ownership, and shipping robust products in fast-moving environments, we would love to hear from you. • Please note that when you submit an application, your data will be processed in line with our privacy policy https://groundtruthlabs.com/privacy.

Responsibilities

• Design, develop and implement advanced deep-learning models to extract valuable insights from histology imaging data • Collaborate with cross-functional teams, including engineers, clinical experts, and product managers, to identify opportunities for data-driven solutions and interpretable algorithms that address clinical questions • Develop and maintain scalable data pipelines and infrastructure to support data science projects. • Manage product, software and clinical and regulatory inputs and requirements to translate research algorithms into clinical-grade tools suitable for use in the real world. • Communicate results and insights to stakeholders and key decision-makers. As well as publicly in research publications and and conference abstracts. • Stay up-to-date with the latest developments in the field of machine learning, medical imaging, and data science

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