Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale - unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone … to accelerate the results that matter. By taking advantage of all structured and unstructured data - securing and protecting private information more effectively - Elastic's complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI. What is the Role Are you looking to make a real impact and play a meaningful role in … focused on excellence; taking the initiative to improve both themselves and the team through continuous learning and questioning the status quo. What Will You Be Doing Architect next-generation search solutions: Design and implement cutting-edge solutions utilizing Elastic's latest advancements in AI, semanticsearch, and vector search, including RAG, vector databases, and other emerging More ❯
environments. AI Development & RAG Implementation Prepare, clean, and structure datasets for fine-tuning LLMs and retrieval-based workflows. Design, implement, and optimise RAG pipelines using vector databases, embeddings, and semanticsearch to connect real-time and historical data to LLMs. Deploy, evaluate, and refine AI agents using GPU-enabled cloud infrastructure. Build and maintain prompt engineering and evaluation … in large-scale web crawling & scraping . Proficiency in Python and one or more of: Node.js, Go, Java. Deep experience in RAG - from embeddings and vector database design to semanticsearch optimisation and retrieval integration with LLMs. Experience with LLM fine-tuning and evaluation. Hands-on experience with GPU cloud platforms for model training and inference. Understanding of More ❯
AI/ML models at scale. To succeed in this role, you'll bring hands-on experience developing and deploying machine learning solutions, especially in areas such as ranking, search, recommendations, and personalization. You'll also demonstrate a strong understanding of user behavior data and how to use it to influence product development. A product mindset and ability to … innovative, international team and workplace that encourages learning and growth. Who you are: Experience working in a Data Science or Machine Learning role, ideally on consumer-facing products like search, ranking, recommendations, personalization, or discovery. Strong hands-on ability with ML modeling, including semanticsearch, ranking algorithms, clustering, recommendation systems, and natural language processing (NLP), with a More ❯
via APIs with input/output filtering and logging Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semanticsearch and retrieval Implementation of grounding, context injection, and response validation mechanisms Model Context Protocol (MCP) Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual memory More ❯
via APIs with input/output filtering and logging Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semanticsearch and retrieval Implementation of grounding, context injection, and response validation mechanisms Model Context Protocol (MCP) Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual memory More ❯
data science, and behavioural modelling to drive meaningful insights and innovations. As AI agents become the norm in this industry, so does the need for efficient legal information retrieval, semanticsearch capabilities, and structured knowledge representation. Your work will bridge the gap between advanced search technologies and the complex information needs of the legal domain, making legal … engineering legal knowledge base construction specialised embedding methods for multimodal content in the legal domain Develop methods for retrieval and reasoning over legal knowledge bases and systems (e.g. hybrid search approaches combining symbolic and neural techniques, query understanding and rewriting for legal search) Performing fine-tuning and reinforcement learning to teach language models how to interact with new More ❯
data science, and behavioural modelling to drive meaningful insights and innovations. As AI agents become the norm in this industry, so does the need for efficient legal information retrieval, semanticsearch capabilities, and structured knowledge representation. Your work will bridge the gap between advanced search technologies and the complex information needs of the legal domain, making legal … engineering legal knowledge base construction specialised embedding methods for multimodal content in the legal domain Develop methods for retrieval and reasoning over legal knowledge bases and systems (e.g. hybrid search approaches combining symbolic and neural techniques, query understanding and rewriting for legal search) Performing fine-tuning and reinforcement learning to teach language models how to interact with new More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
Qdrant is a leading open-source vector search engine designed for applications powered by embeddings and generative AI. We help developers and enterprises unlock the full potential of semanticsearch, recommendation systems, and real-time machine learning applications. We are growing fast and looking for passionate, curious, and driven team members who want to help shape the … looking for a skilled AI Engineer who thrives at the intersection of deep technical development and community collaboration. You'll play a dual role - driving innovation in AI-driven search and vector database technologies, while also engaging directly with our customers, developer community, and broader AI ecosystem. This is a unique opportunity to combine engineering excellence with external advocacy … to open-source projects or engaging with developer communities. Comfortable presenting and participating in public forums, events, or customer meetings. Bonus Points Contributions to AI infrastructure, vector databases, or search systems. Experience building ML-powered products in production. Knowledge of large language models (LLMs) and retrieval-augmented generation (RAG). Public speaking or published technical content (talks, blog posts More ❯
South East London, London, United Kingdom Hybrid / WFH Options
Stepstone UK
and be part of reshaping the labour market and becoming the worlds leading job platform. Job Description Join our team and youll be responsible for our recommender systems and search algorithms,building the core infrastructure that powers millions of meaningful connections. Working in theSearch & Match domain, you willbe focusing on deploying and scaling machine learning models, particularly large language … models in the cloud, particularly with AWS and SageMaker Understanding of DevOps processes and tools: CI/CD, Docker, Terraform, and monitoring/observability Bonus: experience with vector databases, semanticsearch, or event-driven systems like Kafka Additional Information Were a community here that cares as much about your life outside work as how you feel when youre More ❯
and contribute to a collaborative team Nice to Have: Experience with SQL/NoSQL databases Familiarity with MLOps tools (Docker, Git, CI/CD) Exposure to vector databases or semanticsearch Knowledge of financial datasets or document processing workflows If you’re excited to grow your skills in machine learning and work on technology that helps people understand More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
and contribute to a collaborative team Nice to Have: Experience with SQL/NoSQL databases Familiarity with MLOps tools (Docker, Git, CI/CD) Exposure to vector databases or semanticsearch Knowledge of financial datasets or document processing workflows If you’re excited to grow your skills in machine learning and work on technology that helps people understand More ❯
london, south east england, united kingdom Hybrid / WFH Options
Intellect Group
and contribute to a collaborative team Nice to Have: Experience with SQL/NoSQL databases Familiarity with MLOps tools (Docker, Git, CI/CD) Exposure to vector databases or semanticsearch Knowledge of financial datasets or document processing workflows If you’re excited to grow your skills in machine learning and work on technology that helps people understand More ❯
london (city of london), south east england, united kingdom Hybrid / WFH Options
Intellect Group
and contribute to a collaborative team Nice to Have: Experience with SQL/NoSQL databases Familiarity with MLOps tools (Docker, Git, CI/CD) Exposure to vector databases or semanticsearch Knowledge of financial datasets or document processing workflows If you’re excited to grow your skills in machine learning and work on technology that helps people understand More ❯
/Slack/Notion). Disciplined towards best practice version control, CI/CD and code extensibility. Values 'interface safety' through dimensionality reduction at interfaces. Exceptional at 'breadth-first search' through Googling when tackling new challenges, and consistently mindful of local maxima. Intellectually curious with a growth mindset - able to tackle entirely novel challenges that lack prior precedent through … training & validation architecture to prod, so that we can correctly eat up our '1.0' systems at the right time Build cutting edge products like global context aware chat with semanticsearch, care orchestration and LLM-enabled cloud telephony e2e Hire/scale the team, while implementing the right processes at the right times to maximise discounted team productivity More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯
to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semanticsearch, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is More ❯