7 of 7 Permanent Synthetic Data Jobs in Central London

CI/CD pipelines (e.g., GitLab), ensuring both per-commit and nightly execution coverage. Develop resilient, self-healing scripts compatible with Redwood UX and quarterly Oracle updates. Manage test data strategy, including synthetic data generation, GDPR compliance, and reusable datasets. Maintain test traceability by mapping test cases to Jira stories, acceptance criteria, and business processes. Follow Tosca … best practices: version control, test data management, test case design, and virtualization. Collaborate closely with development, product, and DevOps teams to ensure QA automation aligns with sprint and release objectives. Required Skills & Experience Strong hands-on experience with Tosca: model-based testing, test case design, test data management, and business component reuse. In-depth knowledge of Oracle Fusion … preferred or equivalent experience). Strong understanding of modular and scalable automation design principles. Preferred Qualifications Experience working in agile, DevOps-driven teams. Familiarity with GDPR compliance and test data privacy best practices. Strong problem-solving and troubleshooting abilities for automation issues. Diversity & Inclusion At Scrumconnect Consulting, we believe that diversity drives innovation. We are committed to creating an More ❯

Avaloq Software Engineer to join our Wealth Practice in the UK. In this role, you'll play a key part in designing, developing, and maintaining high-quality software and data structures to support our evolving data platforms. You'll collaborate across teams to support data migration, cleansing, enrichment, scripting, and reconciliation—ensuring we deliver reliable and scalable … expertise in Avaloq technologies, database management, and software development—combined with a solid understanding of the Avaloq Enterprise-Wide Object Model—will be critical in shaping and enhancing our data capabilities. This is a fantastic opportunity to bring your passion for innovation into a fast-paced, dynamic environment where your impact will be tangible. Skills Must have You will … have between 5+ years experience working as an Avaloq Developer. Mapping physical data from Avaloq and other platforms to the Enterprise Data Model, ensuring adherence to reference data standards and clear conceptual definitions. Experience with external API integration. Reviewing and optimizing Avaloq APDM outcomes, defining treatment strategies, and improving system performance. Integrating the Avaloq APDM with external More ❯

achieves success. The role: Lead CV Model Development — Design, train, and optimise detection, recognition, segmentation, and tracking models, balancing accuracy, speed, and robustness for real-world retail environments. Enhance synthetic data pipelines to improve generalisation and domain adaptation. Advance Large Vision Models (LVM) — Improve performance, scalability, and adaptability of our in-house LVM for diverse retail use cases. … Contribute to benchmarking and ongoing improvements. Collaborate Across Teams — Work with Product, Infrastructure, and Customer teams to integrate models into workflows. Provide technical leadership aligned with business goals. Champion Data & MLOps — Maintain high data quality standards and develop scalable automation systems for seamless deployment and experimentation. Lead a team of ML Engineers Requirements PhD (or equivalent) in Computer … record deploying large-scale CV models in production. Strong Python skills with PyTorch or TensorFlow expertise. Deep understanding of modern CV architectures, especially LVMs and Transformers. Experience with multimodal data (images, video, text) and MLOps workflows. Hands-on, self-directed, evidence-driven, and collaborative, with excellent communication skills for both technical and non-technical audiences This is an excellent More ❯

making, and control. Integrate AI algorithms into both enterprise-scale and edge-deployed systems . Work with customers to translate complex problems into AI-powered solutions . Lead on data strategy , from collection and simulation to training and validation. Ensure AI safety, ethics, explainability , and compliance with defence standards. Define best practices in MLOps , model evaluation, and continuous integration. … fusion . Excellent communication and problem-solving skills. Desirable Extras Publications in leading AI/ML or robotics conferences (e.g. NeurIPS, CVPR, ICLR, ICRA). Experience with MLOps pipelines, synthetic data, and model optimisation for edge devices . Understanding of sensor fusion, perception pipelines , and AI safety principles . What’s on Offer Highly competitive base salary. Generous More ❯

of their applied AI and research strategy. The role Lead the development of computer vision models (2D/3D pose estimation, video analysis, biomechanics). Apply Generative AI techniques (synthetic data, video generation, code generation, intelligent agents) to improve automation, scale, and personalisation. Manage and mentor a small, specialist team. Define the AI/ML innovation strategy across … Ensure robustness, accuracy, and real-time performance of deployed models. Keep pace with emerging research and technologies, bringing new ideas into production. Partner with domain experts to translate biomechanical data into actionable insights. What we’re looking for Strong background in computer vision and video-based deep learning, (ideally pose estimation, biomechanics or human movement) Proven technical leadership experience More ❯

build fair face-matching and deepfake-detection models. Train and benchmark large-scale vision-language models for document extraction. Train a multi-modal document understanding model from scratch using synthetic data. Optimise LoRA adapter latency in PEFT/Triton. Profile, debug and improve model training speed on multiple GPUs. Create a large-scale dataset for deepfake detection. Experiment with More ❯

build fair face-matching and deepfake-detection models. Train and benchmark large-scale vision-language models for document extraction. Train a multi-modal document understanding model from scratch using synthetic data. Optimise LoRA adapter latency in PEFT/Triton. Profile, debug and improve model training speed on multiple GPUs. Create a large-scale dataset for deepfake detection. Experiment with More ❯