26 to 38 of 38 Synthetic Data Jobs in England

About Arondite Arondite enables organisations to wield autonomy, data and AI at scale. We equip operators with the foundational software to orchestrate their mix of platforms and capabilities, and then take mission-critical decisions faster than their adversaries. We exist to ensure the UK and its allies out-think … edge devices in the field. The role will also encompass addressing the wider practicalities and challenges in implementing AI-based systems, including obtaining training data, addressing ethical concerns and explaining model behaviours. As an early member of the AI team at Arondite, you will be able to shape ...

tackle challenging problems including: Semantic chunking for long, complex documents Information extraction and document enrichment Knowledge graph construction Entity linking and retrieval optimisation Synthetic data generation Knowledge distillation and efficient production LLM/SLM deployment The work sits at the intersection of applied research and production engineering—developing ...

Language Models (LLMs) and Vision-Language Models (VLMs), enabling agents to perceive, understand, and act within complex environments. We own the entire pipeline including synthetic data generation, environment design, mid-training, supervised fine-tuning, offline reinforcement learning, online reinforcement learning, reward modelling, transition modelling, etc. Our team also … advanced LLMs and VLMs, including multimodal architectures Research and implement training methods for enhanced capabilities like instruction following and tool use Design and optimize data pipelines and training systems for large-scale distributed training Collaborate with cross-functional teams to integrate models into agentic AI systems Evaluate model performance ...

seeking a Director of Platform Management for Simulation, Evaluation & Validation to own the product vision for the AI Driver platforms, including simulation, evaluation, synthetic data, and validation workflows. You will lead PMs across teams, define multi-year strategy, drive roadmap end-to-end, and partner with engineering, data ...

audiences think, feel, and respond — without the cost, delay, or limitations of traditional research. We build large-scale simulated populations grounded in real-world data, enabling clients to test messages, strategies, and concepts. Our clients love the ability to receive insights backed by millions of responses in hours rather … evaluation frameworks that go beyond standard benchmarks. You’ll develop rigorous statistical methods to prove the fidelity of our simulations — measuring how well our synthetic populations mirror real-world opinion distributions, demographic patterns, and response dynamics. Advance the state of the art — stay at the frontier of relevant research ...

Function Calling, and A2A to practical enterprise use cases. Engineer robust pipelines for prompt design, context handling, embeddings, chunking strategies, and real-time data integration. Evaluate, test, and optimize model output and application performance to improve relevance, robustness, fairness, and explainability. Implement guardrails, prompt testing, adversarial and bias testing … including Azure OpenAI and Azure AI Search. Ensure solutions are secure, reliable, observable, maintainable, and well documented. Understanding of alignment and feedback techniques, synthetic data generation, and continuous human-in-the-loop review loops. Experience designing evaluation approaches for relevance, groundedness, explainability, safety, robustness, and operational quality. Experience ...

building 0-to-1 systems, pipelines, and scalable infrastructure. Preferred qualifications: Experience engineering search and retrieval pipelines, time-series workflows, or simulation environments with synthetic data generators. Experience working alongside research teams to convert groundbreaking, open-ended research ideas into robust prototypes and production-grade products. A demonstrated … institutes all over the world. From creating experiments and prototyping implementations to designing new architectures, engineers work on real‐world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. ...

eval methodology — task and repo-level evals, dataset curation, the craft of measuring what actually matters. Outer-loop and pipeline thinking — feedback loops, training-data flywheels, bandit-style optimisation, anything that goes beyond a single agent session. Failure-mode analysis — instrumenting agents, reading traces at volume, surfacing patterns engineering … Direct experience with coding agents or code-generation systems. Background in RL, bandits, or other outer-loop optimisation frameworks applied to LLMs. Experience building synthetic data, dataset infrastructure, or internal tooling that other engineers actually used. A project you can show us (GitHub links welcome) and a thoughtful ...

complex and contested environments. A successful candidate will be skilled in developing real-time object detection, sensor fusion, and state estimation algorithms using data from diverse mission sensors such as EO/IR cameras, radars, and IMUs. The role requires strong algorithmic thinking, deep familiarity with airborne sensing systems … perception algorithms - Design and implement robust algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities. Implement sensor fusion frameworks - Integrate data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness. Develop state estimation capabilities - Design ...

benchmark from scratch that distinguished specific model capabilities (i.e., produced a measurable, defensible capability difference, not just a score). Have built synthetic data for post-training textual or multimodal models. Can reproduce a published benchmark result and identify where the original methodology is fragile or misleading. ...

large-scale experiments, and drive breakthroughs into production. You will develop models that reason about document layout by fusing expert, real world and synthetic data, while leading efforts to make our #J-18808-Ljbffr ...

Lead to own the pretraining stage of our VLM/VLA framework powering a fleet of robots across platforms. Define base model strategy, data mixtures, and scaling, leading research engineers training foundation policies on diverse real-world and synthetic data. You will design large-scale distributed training, establish … evaluation suites, and collaborate with MLOps and Data Platform teams to ensure smooth transfer to post-training and real-robot inference. #J-18808-Ljbffr ...