Own backend features and API integrations (Python, FastAPI, gRPC, SQL) Adapt and extend auto-generated pipelines and front-end outputs Build connectors for APIs, files, and external systems Integrate LLM-based capabilities with robust evaluation and monitoring Champion AI-assisted development practices and tools Set up guardrails and context packs for AI-powered workflows Mentor team members on AI development More ❯
Own backend features and API integrations (Python, FastAPI, gRPC, SQL) Adapt and extend auto-generated pipelines and front-end outputs Build connectors for APIs, files, and external systems Integrate LLM-based capabilities with robust evaluation and monitoring Champion AI-assisted development practices and tools Set up guardrails and context packs for AI-powered workflows Mentor team members on AI development More ❯
research to UX, UI, and prototyping. Collaborate with front-end developers to ensure accessible, scalable, and sustainable design implementation. Partner with data engineering and AI teams to integrate NLP, LLM, and advanced analytics into user workflows. Define and evolve visual languages, data visualisation systems, and design standards across products. Use qualitative and quantitative research to inform design decisions and prioritisation. More ❯
research to UX, UI, and prototyping. Collaborate with front-end developers to ensure accessible, scalable, and sustainable design implementation. Partner with data engineering and AI teams to integrate NLP, LLM, and advanced analytics into user workflows. Define and evolve visual languages, data visualisation systems, and design standards across products. Use qualitative and quantitative research to inform design decisions and prioritisation. More ❯
drive data collection: specify what “good” looks like, ensure diversity/coverage, and close the gap between sim and real. Run pre-/mid-/post-training on multimodal LLM/VLM/VLA stacks; plug in new modalities (vision, audio, proprioception, LiDAR/point clouds, ...) without breaking existing ones. Build and maintain continuous pipelines: ingest simulation + tele More ❯
drive data collection: specify what “good” looks like, ensure diversity/coverage, and close the gap between sim and real. Run pre-/mid-/post-training on multimodal LLM/VLM/VLA stacks; plug in new modalities (vision, audio, proprioception, LiDAR/point clouds, ...) without breaking existing ones. Build and maintain continuous pipelines: ingest simulation + tele More ❯
Senior AI Engineer to design, build, and deploy advanced AI and machine learning solutions for a leading research platform. This is a hands-on role focused on production-grade LLM applications, AI-enabled workflows, and augmented intelligence solutions. You will collaborate closely with engineering, research, analytics, and product teams to drive innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval … Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with LangChain/LangGraph; apply multimodal AI, prompt engineering, fine-tuning, and model optimization; ensure scalable, reliable, and … contribute to architecture, POCs, and production services; mentor junior engineers; stay updated with AI/ML and domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Revoco
Senior AI Engineer to design, build, and deploy advanced AI and machine learning solutions for a leading research platform. This is a hands-on role focused on production-grade LLM applications, AI-enabled workflows, and augmented intelligence solutions. You will collaborate closely with engineering, research, analytics, and product teams to drive innovation and deliver impactful solutions. Key Responsibilities: - Data & Retrieval … Build ingestion pipelines for structured and unstructured data; design retrieval-augmented generation (RAG) systems; manage vector and keyword indexes; develop NLP and recommendation systems; implement metadata and tagging frameworks. - LLM & ML Applications: Develop and maintain ML and LLM models; build LLM apps with LangChain/LangGraph; apply multimodal AI, prompt engineering, fine-tuning, and model optimization; ensure scalable, reliable, and … contribute to architecture, POCs, and production services; mentor junior engineers; stay updated with AI/ML and domain trends. Skills & Experience: - Demonstrated hands-on experience building production AI/LLM applications. - Strong Python, API design, asynchronous programming, and integration skills. - Experience with ML/LLM frameworks (PyTorch, TensorFlow, scikit-learn, LangChain/LangGraph, LlamaIndex). - Familiarity with cloud deployment (Azure More ❯
chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy … in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools More ❯
chatbots, document summarization, code assistants, and more. Responsibilities: Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy … in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools More ❯
in the office in London or Edinburgh ; Responsibilities: Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy … in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Luxoft
in the office in London or Edinburgh ; Responsibilities: Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for real-world enterprise use cases. Build and fine-tune LLM-based applications such as: - Chatbots - Document Q&A systems - Report generators - Code assistants - Summarization tools Apply prompt engineering, Retrieval-Augmented Generation (RAG), and context-aware pipelines to enhance model accuracy … in Python (preferred), with experience in Java or Node.js. Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral), Transformers, and Diffusion models. Experience with Hugging Face Transformers, LangChain, LLM orchestration frameworks, and prompt tuning. Familiarity with RAG pipelines, embedding models, and vector databases. Experience with cloud platforms (AWS, GCP, Azure) and AI/ML services. Knowledge of MLOps tools More ❯
Technically sharp AI Prompt Engineer Youll design and optimize prompts, build LLM-powered applications, and deploy scalable GenAI solutions that connect people and intelligent systems in new ways. ?? What Youll Do Design, test, and refine prompts for leading LLMs (GPT-4/5, Claude, Gemini, Mistral, LLaMA, Cohere). Experiment with advanced prompting techniques; Chain-of-Thought, ReAct, Tree-of … speed up iteration. Apply MLOps/LLMOps practices with MLflow, Weights & Biases, and Kubeflow. ?? Youll Bring Strong Python skills and experience with LangChain, Transformers, Hugging Face. Solid grasp of LLM behavior, prompt optimization, and data engineering. Familiarity with vector databases (FAISS, Pinecone, ChromaDB). Hands-on with Linux, Bash/Powershell scripting, cloud environments. Creative problem-solver with excellent communication More ❯
search, entity recognition, and relationship extraction. Design and implement intelligent tagging and metadata enrichment frameworks to categorize and organize legal and market data, improving search, discoverability, and insight accuracy. LLM & Machine Learning Application Engineering Design, build, and maintain traditional ML and LLM models and pipelines. Build LLM apps using LangGraph/LangChain: tools/function calling, structured outputs (JSON Schema … landscape and legal-tech/legal-analytics domain to bring relevant innovations into our stack. Skills and Experience Professional experience Demonstrable experience in software engineering, with 2+ years building LLM/AI applications in production. Strong in Python, API design, asynchronous programming, and integration patterns. Proven ability to scale LLMs and other AI models for high-volume, real-world applications … including optimising inference, managing computational resources, and ensuring reliability and maintainability. Programming & ML/LLM Frameworks Strong expertise in Python and relevant ML/LLM libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn). Strong in Python, API design, asynchronous programming, and integration patterns. Hands-on with LangGraph/LangChain, LlamaIndex or Semantic Kernel for orchestration (tools, agents, guards, structured More ❯
cleaning data all the way to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., Hugging Face Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based More ❯
cleaning data all the way to monitoring models in production Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers Experience building automated data pipelines Hands-on experience with LLM tooling and libraries (e.g., Hugging Face Transformers/PEFT, tokenisers, spaCy or similar) Experience shipping NLP systems: prompt engineering, fine-tuning (e.g., LoRA/PEFT), vector search, and RAG-based More ❯
end-to-end Ship fast and see your work used by real customers immediately Help define the technical architecture and product roadmap Experiment with AI-driven automation and large-language-model workflows Tech: TypeScript, React, Node, GraphQL, AWS, Temporal, LangChain (They're open to Engineers from any language background, as long as you're happy in this tech environment). More ❯
end-to-end Ship fast and see your work used by real customers immediately Help define the technical architecture and product roadmap Experiment with AI-driven automation and large-language-model workflows Tech: TypeScript, React, Node, GraphQL, AWS, Temporal, LangChain (They're open to Engineers from any language background, as long as you're happy in this tech environment). More ❯
London, England, United Kingdom Hybrid/Remote Options
iO Associates
teams ☑️ Optimise agent behaviour via feedback and user interaction ☑️ Evaluate performance and maintain safety mechanisms ☑️ Document agent logic, design, and dependencies Key Skills & Experience: ☑️ Proven experience designing and refining LLM prompts and AI agents ☑️ Strong analytical skills for assessing outputs and interactions ☑️ Experience managing prompt libraries and best-practice templates ☑️ Effective cross-functional collaboration and communication ☑️ Familiarity with evaluation frameworks More ❯
Excellent communication skills and the ability to produce clear technical documentation Enthusiasm for working in an early-stage, fast-moving startup environment Why Apply Work on innovative AI and LLM-driven products with real client traction Short-term engagement with long-term growth potential Opportunity for equity participation and lead developer involvement Interested? Apply now or reach out directly to More ❯
Excellent communication skills and the ability to produce clear technical documentation Enthusiasm for working in an early-stage, fast-moving startup environment Why Apply Work on innovative AI and LLM-driven products with real client traction Short-term engagement with long-term growth potential Opportunity for equity participation and lead developer involvement Interested? Apply now or reach out directly to More ❯
world impact. Experience in early-stage or startup environments is a plus. A “builder” mindset; you’re happiest when ideas turn into working systems. Key Experience: Agentic System Design LLM Engineering/Foundation Models Planning and Reasoning Scalable ML Infrastructure Reinforcement Learning (esp. RLHF/RLAIF) Simulation or feedback-driven adaptation Interview Process Initial Chat – Conversation with a Founder Technical More ❯
world impact. Experience in early-stage or startup environments is a plus. A “builder” mindset; you’re happiest when ideas turn into working systems. Key Experience: Agentic System Design LLM Engineering/Foundation Models Planning and Reasoning Scalable ML Infrastructure Reinforcement Learning (esp. RLHF/RLAIF) Simulation or feedback-driven adaptation Interview Process Initial Chat – Conversation with a Founder Technical More ❯
to code quality. Comfortable working on-site in a fast-paced, collaborative startup. Nice to Have Experience with data-heavy or high-throughput systems. Exposure to applied AI or LLM integrations (no model training required). Familiarity with GCP , especially IAM, networking, and security. Why Electric Twin Impact – Shape both the product and how we build it. Pace – We ship More ❯
to code quality. Comfortable working on-site in a fast-paced, collaborative startup. Nice to Have Experience with data-heavy or high-throughput systems. Exposure to applied AI or LLM integrations (no model training required). Familiarity with GCP , especially IAM, networking, and security. Why Electric Twin Impact – Shape both the product and how we build it. Pace – We ship More ❯
