AI Systems Developer

scientists, platform engineers, and other domain experts across the organisation. Depending on priorities, the engineer may work within a specific ML team or operate in a cross-functional capacity.Based at the company's wet/dry lab and headquarters in central London, the role involves working with large datasets, complex models, and high-performance compute. The engineer will strengthen training and inference pipelines, improve software foundations, and optimise the hybrid on-prem/cloud environment, including dedicated DGX clusters and collaborations with partners like NVIDIA.ResponsibilitiesWork with interdisciplinary teams to solve challenges across data engineering, ML engineering, and software engineeringBuild and improve data processing, transformation, and loading systems to support model training and inference at scaleDevelop and maintain high-quality research and production codebases to enable rapid, reproducible experimentationAdvance software engineering practices by, The Role: AI Engineer (London based)We're seeking exceptional AI Engineers who can operate at the intersection of cutting-edge AI technology and real-world business impact. This isn't about building demos or proofs-of-concept. You will own end-to-end development of..., Role: AI EngineerLocation: LondonSalary: £70-£80kI'm currently partnering with an innovative financial services company that's looking to hire a hands-on AI Engineer to work directly with clients and take AI solutions from concept through to production.This isn't a...

optimising systems, streamlining pipelines, and improving robustness across workflowsEducation & ExperienceBSc/MSc/PhD in Computer Science, Machine Learning, Engineering, or related field2+ years of industry experienceCore SkillsSolid understanding of algorithms, data structures, and computational complexityProficiency in Python with clean, maintainable coding practicesFamiliarity with PyTorch and common scientific Python librariesMachine Learning ExpertiseSolid understanding of ML fundamentals and modern deep learningExperience training, evaluating, and iterating on modelsInfrastructureFamiliarity with AWS or GCP, Docker, Kubernetes, and CI/CDFamiliarity with orchestration tools (Airflow, Prefect) and model-serving frameworksNice to HaveExposure to biology, bioinformatics, or machine learning for scientific domainsPersonal AttributesCollaborative team player, able to communicate effectively with stakeholders from diverse backgrounds and technical abilitiesPassionate about science and making a real difference for patientsSelf-motivated, curious, and driven to succeedUser-minded: considers how datasets and models will be used downstreamComfortable working independently and taking initiativeWhy JoinWork in a highly collaborative, interdisciplinary environmentAccess to state-of-the-art wet and dry lab facilities in central LondonShape the systems and infrastructure that support cutting-edge ML researchContribute directly to advancing drug discovery and improving patient outcomesThe company is a committed equal opportunities employer and welcomes applicants from all backgrounds. Similar jobs

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