Future Tech Jobs
Future Tech Jobs
Design and build full-stack applications that integrate AI-driven physics simulation models into real-world engineering workflows. Collaborate directly with customers and technical teams to prototype, deploy, and iterate on high-impact tools across aerospace, energy, and advanced manufacturing. Work across backend services, APIs, and cloud infrastructure while contributing to core platform development.
This role involves building and running high-fidelity CFD simulations from geometry preparation to post-processing for moderately complex engineering cases. You'll work at the intersection of CAE and data science, supporting the development of AI-driven simulation models and contributing to automated workflows on cloud and HPC platforms. The position includes customer collaboration, model adaptation for deep learning surrogates, and occasional international travel to support on-site engagements.
Design and deploy production-grade machine learning systems for high-impact clients in national security and AI safety. Develop scalable ML infrastructure, lead technical architecture decisions, and translate complex AI concepts for stakeholders. Work across the full ML lifecycle from prototyping to deployment using modern cloud and containerisation technologies.
Design and build scalable, production-grade machine learning systems for high-impact clients in national security and AI safety. Lead technical architecture, deploy secure AI solutions on cloud platforms, and mentor engineering teams. Work cross-functionally to translate complex AI concepts into operational systems while adhering to rigorous ethical and security standards.
This role involves leading translational biology strategies in oncology and immunology, bridging AI-driven drug design with experimental validation. You will design in vivo pharmacology studies, develop biomarker strategies, and manage CRO partnerships to generate robust data for clinical translation. The position plays a key role in advancing drug candidates from discovery through to clinical development by integrating biological insights with machine learning predictions.
A Research Scientist will focus on applying Large Language Models to drug discovery challenges, developing novel ML techniques and models that integrate with biological and chemical data. The role involves close collaboration with interdisciplinary teams of scientists and engineers to advance AI-driven drug design. Work includes model development, experimentation, and scaling frameworks for predictive applications in a fast-paced research environment.
This role involves developing and automating high-throughput functional genomics assays using primary and co-culture cell models to study fibrotic diseases. The scientist will integrate multimodal readouts—including transcriptomics, proteomics, and imaging—to capture cellular responses in perturbation studies, working closely with machine learning and automation teams. Key responsibilities include assay optimisation, data analysis, and translating manual workflows into scalable, automated platforms.
Lead the design, execution, and interpretation of in vivo pharmacology studies to support drug discovery programmes, primarily in osteoporosis but extending across indications. Partner with CROs to deliver preclinical data, integrate in vitro and ex vivo assays, and translate biological insights into project decisions within a multidisciplinary TechBio environment.
This role involves conducting empirical research into the capabilities of specialised biological AI models, particularly in protein design and genomics, to assess their potential for misuse. The researcher will design experiments to evaluate in-silico predictions against real-world biological outcomes, test the effectiveness of technical safeguards, and translate findings into actionable insights for government and policy stakeholders. Work spans machine learning, computational biology, and biosecurity, requiring close collaboration with wet-lab scientists, AI developers, and security experts.
Develop an AI-powered biomarker discovery engine using multi-modal biomedical data, including EHRs, wearables, and multi-omics, to enhance disease risk prediction. Focus on time series analysis, data fusion, and cost-effective discovery while embedding expertise within the partner company. Contribute to academic publications and model deployment in a precision medicine context.
This role involves designing and prototyping generative machine learning models for protein design, with a strong focus on real-world biological applications. The scientist will build and evaluate models, collaborate across interdisciplinary teams, and iterate based on wet lab feedback. A significant emphasis is placed on high-performance code, scalable data pipelines, and staying current with advances in ML and synthetic biology.
Design and engineer functional proteins using proprietary generative AI models, bridging machine learning and experimental validation teams. Analyze structural biology and sequence data to generate and refine protein designs, then collaborate closely with wet lab scientists to test and iterate on results. Contribute to model improvement, data systems, and scientific knowledge sharing in a high-impact synthetic biology environment.
Design and operate scalable cloud infrastructure for AI and agentic systems, with a focus on model serving and production reliability. Build cloud-native solutions using GCP technologies and support scientists with robust, high-performance services. Work across the full software lifecycle in an agile environment alongside ML engineers and domain experts.
This role involves developing end-to-end machine learning systems integrated with advanced electronics for defence and security applications. You'll work across diverse domains such as computer vision and generative models, building functional prototypes and demonstrators. The role emphasizes innovation, rapid iteration across projects, and close collaboration in a technically driven, low-management environment.
Lead high-value enterprise opportunities through the joint AWS and OpenAI co-sell motion, working closely with AWS field teams and OpenAI stakeholders to shape and close strategic AI and cloud transformation deals. Develop scalable playbooks and value propositions that align OpenAI’s capabilities with enterprise business priorities. Operate in a cross-functional, executive-facing role to drive commercial execution and pipeline growth.
