2 of 2 Remote Machine Learning Scientist Jobs in the City of London

Machine Learning Research Scientist | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN We are looking for multiple highly skilled machine learning researchers with strong expertise in generative modeling is sought to join an interdisciplinary team of machine learning experts, protein engineers, and biologists. The team collaborates to transform how biology is … team is driven by innovation, curiosity, and a commitment to creating significant positive global impact. Requirements Expertise in generative modeling: The ideal candidate has a proven track record in machine learning, with experience leading or contributing to high-profile projects, as evidenced by widely used open-source libraries, major product launches, or impactful publications (e.g., NeurIPS, ICML, ICLR … running models on cloud hardware and parallelizing data and models across accelerators. Data engineering capabilities: The candidate is experienced in building ML data pipelines for training and evaluating deep learning models, including raw data analysis, dataset management, and scalable pipeline construction. Passion for optimization: They possess in-depth knowledge of ML libraries, hardware interactions, and optimization techniques for model More ❯

Machine Learning Research Scientist | Generative Models | Protein Design | Deep Learning | Python | Hybrid, LDN We are looking for multiple highly skilled machine learning researchers with strong expertise in generative modeling is sought to join an interdisciplinary team of machine learning experts, protein engineers, and biologists. The team collaborates to transform how biology is … team is driven by innovation, curiosity, and a commitment to creating significant positive global impact. Requirements Expertise in generative modeling: The ideal candidate has a proven track record in machine learning, with experience leading or contributing to high-profile projects, as evidenced by widely used open-source libraries, major product launches, or impactful publications (e.g., NeurIPS, ICML, ICLR … running models on cloud hardware and parallelizing data and models across accelerators. Data engineering capabilities: The candidate is experienced in building ML data pipelines for training and evaluating deep learning models, including raw data analysis, dataset management, and scalable pipeline construction. Passion for optimization: They possess in-depth knowledge of ML libraries, hardware interactions, and optimization techniques for model More ❯