As a Senior AI Engineer at PoliceAI, you will lead the design, development, and deployment of AI-enabled products, translating policing needs into technical solutions. You will work with multidisciplinary teams to build secure, maintainable, and scalable services, and support the testing, evaluation, and validation of AI products.
As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.
Lead or contribute to drug discovery projects by integrating medicinal chemistry expertise with AI-driven platforms. Collaborate closely with machine learning scientists to refine predictive models, guide programs from hit identification to candidate selection, and manage external research partners. The role emphasizes innovation in structure-based and fragment-based design within a dynamic, interdisciplinary environment.
This role involves leading drug discovery programs using AI-first approaches, combining computational chemistry expertise with machine learning to accelerate the design of novel therapeutics. The candidate will guide projects from initiation to candidate selection, collaborate across disciplines, and help shape the evolution of Isomorphic Labs' AI platform. Opportunities exist for both scientific leadership and people management, with a focus on innovation in molecular design and strategic problem-solving.
This role involves developing and evaluating AI algorithms to quantify iron distribution in the brain using MRI data. The position is part of a multi-disciplinary research group at UCL, focusing on advancing healthcare technology through computational and medical sciences.
Conducts original research in AI safety, focusing on interpretability and behavioral analysis of transformer-based large language models. Designs and runs experiments, develops reproducible research tooling in Python/PyTorch, and translates technical findings for government, frontier labs, and national security partners. Publishes results in academic papers and technical reports while collaborating with senior scientists to shape emerging AI safety standards.
As a Research Scientist, you will work on the cutting edge of generative AI, focusing on interactive avatars that can engage in natural, real-time conversations. Your responsibilities will include advancing the state of the art in dyadic interaction modeling, post-training multimodal models, and building robust evaluation frameworks.
The role involves deploying and optimizing cutting-edge AI models for real-time inference, focusing on performance, reliability, and scalability. You'll work across the stack to improve latency, throughput, and cost efficiency, building high-performance serving systems and tooling that bridge research and production. The position emphasizes autonomous problem-solving and deep optimization in GPU and ML infrastructure environments.
This role involves building and operating large-scale, distributed web crawlers to source high-quality data for training frontier AI models. The engineer will solve challenges in content extraction, deduplication, and recrawl strategies, while designing pipelines for multilingual and multimedia content. They will also develop tooling for researchers to access and monitor crawled data efficiently.
This role involves designing and running large-scale reinforcement learning experiments to understand scaling effects across model size, compute, and task horizon. The engineer will build benchmarks for long-horizon RL, debug system-level issues at the research-infrastructure boundary, and translate validated findings into production training recipes. Work is highly collaborative with research and engineering teams, focusing on empirical science to advance steerable and safe AI systems.
This role involves hands-on lab work in cell biology, including designing and executing cellular and biochemical assays, maintaining cell lines, and analyzing data. You will work in a highly interdisciplinary team, contributing to the discovery of novel drug targets and advancing your skills in assay development and optimization.
The role involves conducting research at the intersection of machine learning and quantitative finance, focusing on the development and application of modern machine learning and statistical methods to financial market problems. The post holder will work under the supervision of Professors Álvaro Cartea and Mihai Cucuringu, contributing to research methodologies and preparing outputs for publication.
This role involves developing and evaluating machine learning models to predict Strep A outbreaks using real-world datasets. You will collaborate with clinicians and an engineering team to create a tool that can provide early warnings to public health teams.
This role involves leading the technical development of a research platform that harmonizes data from multiple sources using NLP technologies. You will work within a multidisciplinary team to implement new features, maintain existing software, and ensure the platform meets commercial standards.
This role involves collaborating with Cohere researchers on cutting-edge machine learning research, building and training large language models, and contributing to research initiatives with practical applications in product development. The intern will work on projects related to base model training, retrieval augmented generation, data and evaluation, safety, and finetuning.
This role involves owning a research work-stream focused on 3D geometry representation and generation, designing and training generative models, and working with ML and simulation engineers to solve complex engineering challenges. The position requires a PhD in a relevant field and expertise in generative models, geometric deep learning, and 3D vision.
This role involves collaborating with researchers and engineers to advance the capabilities and safety of large language models through reinforcement learning. Responsibilities include developing core RL infrastructure, designing novel training environments, and optimizing performance across the stack.
