Future Tech Jobs
Future Tech Jobs
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, focusing on the Cosmos World Foundation Models. You will work closely with research scientists, software engineers, and hardware experts to improve inference speed and deploy models in production settings.
This role involves optimizing and deploying deep learning models for high-performance inference on GPU platforms, working closely with research scientists, software engineers, and hardware experts. The focus is on improving inference speed and profiling deep learning workloads to identify and remove bottlenecks.
This role involves developing and deploying deep learning models, particularly for sequential data, to enhance underwriting systems and support the integration of Large Language Models in customer-facing products. The candidate will work cross-functionally with tech and product teams, using Python and modern ML frameworks to extract insights from complex structured and unstructured datasets. Collaboration, innovation, and applying advanced machine learning techniques to real-world lending challenges are central to the position.
Develop and deploy deep learning models to enhance underwriting and lending systems, with a focus on sequential data and multimodal inputs. Collaborate with product and tech teams to integrate Large Language Models into customer-facing solutions. Work across structured and unstructured data to deliver actionable insights that drive business growth and innovation.
As a Senior Machine Learning Engineer, you will lead the deployment of AI models and engineering surrogates to customer production environments, working closely with Data Scientists, Simulation Engineers, and customers. You will drive technical decisions, mentor team members, and travel to customer sites to build solutions on-site, ensuring practical and impactful outcomes.
As a Machine Learning Engineer, you will collaborate with Data Scientists, Simulation Engineers, and customers to solve complex engineering and physics challenges. You will design, build, and test reliable, scalable ML data pipelines, manipulate 3D point cloud and mesh data, and ensure the successful deployment of AI models in real-world applications.
This role involves developing novel machine learning models and algorithms to accelerate drug discovery through AI. You'll work in an interdisciplinary environment, applying deep learning techniques to complex biological and chemical problems, while collaborating closely with scientists and engineers. The focus is on creating scalable, cutting-edge AI solutions that advance rational drug design.
A Research Scientist in Machine Learning will develop novel deep learning models and algorithms to advance drug discovery at digital speed. Working in an interdisciplinary team, they will apply cutting-edge AI techniques to complex biological and chemical problems, iterating on model design, training, and inference to unlock new scientific insights. The role emphasizes innovation, collaboration, and technical leadership in a high-impact research environment.
Develop and optimize generative machine learning models for protein design, working closely with biologists and engineers to translate model outputs into real-world wet lab experiments. The role emphasizes robust ML development, data pipeline construction, and rapid iteration based on experimental feedback, within an interdisciplinary research environment focused on advancing synthetic biology.
As an Applied Scientist in the Alexa International Tech team, you will develop cutting-edge generative AI and speech synthesis technologies to enhance Alexa's natural and culturally relevant communication across multiple languages. Your work will involve designing and conducting experiments, prototyping new approaches, and collaborating with engineering teams to deploy these models at scale.
Develop and optimize machine learning and computer vision algorithms for real-world perception and intelligence systems. Work on end-to-end development, from data analysis and model experimentation to deployment and workflow automation. Collaborate across teams, mentor colleagues, and contribute to best practices in a technically advanced engineering environment.
This role involves pushing the frontier of large language model (LLM) development, focusing on enhancing model intelligence, efficiency, and capabilities. Responsibilities include designing and scaling new architectures, executing and analyzing experiments, and optimizing model and computational performance.
Research Scientist / Research Engineer - Multimodal AI & Large Language ModelsLocation: LondonSalary: £(phone number removed) per annum + permanent benefits + bonusJob Type: Permanent, Full-Time, On-siteAbout the OpportunityWe are partnering with an innovative research organisation at the forefront of...
This role involves leading the research and development of trustworthy AI systems, focusing on safety, robustness, and efficiency. You will contribute to the Online Safety Research Roadmap, design and evaluate solution architectures, and conduct hands-on experiments in collaboration with a team of experts.
This role involves delivering technical AI and machine learning curriculum through workshops and mentoring, supporting apprentices in developing practical skills aligned with industry needs. The lead will facilitate sessions on topics including data ethics, model deployment, and responsible AI, while contributing to continuous improvement of learning products. A strong emphasis is placed on creating an inclusive, engaging learning environment and guiding apprentices through complex technical concepts in real-world business contexts.
