226 to 250 of 741 Remote LLM Jobs

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences More ❯

Genesys empowers organizations of all sizes to improve loyalty and business outcomes by creating the best experiences for their customers and employees. Through Genesys Cloud, the AI-powered Experience Orchestration platform, organizations can accelerate growth by delivering empathetic, personalized experiences More ❯

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 ❯

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 ❯

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 ❯

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 ❯

applications using the latest frameworks and technologies. Responsibilities Technical Development Develop platform functionality using Python, building APIs and integrations to extend capabilities for diverse client needs. Design and implement LLM-powered applications and workflows using open source models such as Llama, Qwen and Gemma, as well as those online models from OpenAI, Gemini, etc. Build AI agents with tool/… function calling, prompt engineering and appropriate guardrails using frameworks such as OpenAI AgentSDK, LangGraph or LlamaIndex. Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation. Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines. Solution Design and Implementation Design and deliver scalable … members and contribute to technical knowledge sharing within the team. Role Requirements Work Experience At least three years as a software engineer on commercial platforms, with demonstrable experience building LLM-powered applications. Proven experience with API-level LLM usage, including prompt engineering and tool/function calling. Experience with agent frameworks (OpenAI AgentSDK, LangGraph, LlamaIndex Agents or similar). Experience More ❯

applications using the latest frameworks and technologies. Responsibilities Technical Development Develop platform functionality using Python, building APIs and integrations to extend capabilities for diverse client needs. Design and implement LLM-powered applications and workflows using open source models such as Llama, Qwen and Gemma, as well as those online models from OpenAI, Gemini, etc. Build AI agents with tool/… function calling, prompt engineering and appropriate guardrails using frameworks such as OpenAI AgentSDK, LangGraph or LlamaIndex. Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation. Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines. Solution Design and Implementation Design and deliver scalable … members and contribute to technical knowledge sharing within the team. Role Requirements Work Experience At least three years as a software engineer on commercial platforms, with demonstrable experience building LLM-powered applications. Proven experience with API-level LLM usage, including prompt engineering and tool/function calling. Experience with agent frameworks (OpenAI AgentSDK, LangGraph, LlamaIndex Agents or similar). Experience More ❯

applications using the latest frameworks and technologies. Responsibilities Technical Development Develop platform functionality using Python, building APIs and integrations to extend capabilities for diverse client needs. Design and implement LLM-powered applications and workflows using open source models such as Llama, Qwen and Gemma, as well as those online models from OpenAI, Gemini, etc. Build AI agents with tool/… function calling, prompt engineering and appropriate guardrails using frameworks such as OpenAI AgentSDK, LangGraph or LlamaIndex. Implement testing and evaluation frameworks for LLM applications, covering prompt testing, output quality metrics and agent behaviour validation. Apply relevant AI technologies as needed, including retrieval systems (RAG, GraphRAG), knowledge graphs, vector databases or data pipelines. Solution Design and Implementation Design and deliver scalable … members and contribute to technical knowledge sharing within the team. Role Requirements Work Experience At least three years as a software engineer on commercial platforms, with demonstrable experience building LLM-powered applications. Proven experience with API-level LLM usage, including prompt engineering and tool/function calling. Experience with agent frameworks (OpenAI AgentSDK, LangGraph, LlamaIndex Agents or similar). Experience More ❯

user of tools for all main SEO research, reporting, and diagnostic use cases (e.g., keyword research, competitor analysis, bot analysis, scraping, auditing, traffic analysis, analytics, etc.) Awareness of emerging LLM/Search landscape and GEO opportunities Detailed understanding of datasets relevant to the SEO ecosystem Basic proficiency in SQL and Python Additional Information Were a community here that cares as More ❯

ll evaluate (and you'll operate) through this lens: 1) Product Strategy – choose the right problems and move the right metrics Own a core outcome (e.g., activation, early retention, LLM reliability) with a clear thesis and roadmap Tell a metrics story: define baselines, leading indicators, and the sequence of bets to get from A → B Think in systems: map the More ❯

ll evaluate (and you'll operate) through this lens: 1) Product Strategy – choose the right problems and move the right metrics Own a core outcome (e.g., activation, early retention, LLM reliability) with a clear thesis and roadmap Tell a metrics story: define baselines, leading indicators, and the sequence of bets to get from A → B Think in systems: map the More ❯

with backing from top-tier VCs and prominent angel investors. High-trust environment. What They’re Looking For Strong engineering background (ideally 5+ years). Proven experience shipping production LLM systems . Hands-on experience with agentic/multi-step reasoning AI . Familiar with modern AI tooling . Product-first mindset and excited about early-stage startup ownership . More ❯

with backing from top-tier VCs and prominent angel investors. High-trust environment. What They’re Looking For Strong engineering background (ideally 5+ years). Proven experience shipping production LLM systems . Hands-on experience with agentic/multi-step reasoning AI . Familiar with modern AI tooling . Product-first mindset and excited about early-stage startup ownership . More ❯

world problems with the latest in AI and LLMs, this role is for you. In this role, you’ll: 🔧 Build and ship high-impact software 🧠 Work on AI/LLM-powered automation tools used in production 🏗️ Help shape scalable systems and infrastructure 🌍 Work collectively across teams to push the product forward 💻 Be working end-to-end on both backend and More ❯

world problems with the latest in AI and LLMs, this role is for you. In this role, you’ll: 🔧 Build and ship high-impact software 🧠 Work on AI/LLM-powered automation tools used in production 🏗️ Help shape scalable systems and infrastructure 🌍 Work collectively across teams to push the product forward 💻 Be working end-to-end on both backend and More ❯

digital self-expression platforms Familiarity with creative or 3D tooling (Figma, Unity, Unreal, etc.) Background in high-growth consumer apps or UGC ecosystems Exposure to AI/ML or LLM-based product environments Why Join Exponential growth: Be part of a company scaling from tens of millions of users toward hundreds of millions Category-defining innovation: Help shape an emerging More ❯

from data preparation and evaluation to model fine-tuning, inference, and agentic workflows. You'll work closely with product and engineering teams to deliver reliable, cost-effective, and scalable LLM-powered solutions on AWS. What You'll Do End-to-End GenAI Solutions: Scope problems, choose the right approach (prompt engineering, fine-tuning, agents), implement, evaluate, and deploy. Data & SQL … conversations around scaling, monitoring, and maintaining GenAI systems in production environments. Minimum Qualifications 5+ years of Software/ML engineering experience, including 2+ years building and deploying GenAI/LLM systems. MS/PhD in Computer Science, Data Science, or equivalent experience. Strong SQL and Python skills with solid software engineering fundamentals. Experience with agent frameworks (LangGraph, AutoGen, CrewAI) and … tool-driven agents. Hands-on with deep learning (PyTorch or TensorFlow) and LLM fine-tuning (SFT/PEFT like LoRA/QLoRA). Production experience with Docker and AWS (ECS, EKS, SageMaker, Lambda, or GPU services). Experience building scalable data and model pipelines for training and deployment. Familiarity with prompt engineering, evaluation frameworks (LLM-as-judge, metrics), and offline More ❯

combines cutting edge software engineering with the demands of processing petabyte-scale genomic data and orchestrating complex AI workflows. You will create the robust, scalable systems that enable our LLM and Agentic AI components to transform biological research from traditional pipelines to intelligent, autonomous discovery platforms. Key Responsibilities Platform Architecture & Development • Design and implement distributed systems for processing petabyte-scale … modular AI component integration • Create real-time data streaming pipelines for continuous genomic analysis • Implement fault-tolerant systems with 99.99% uptime requirements AI Infrastructure Engineering • Build scalable infrastructure for LLM deployment and inference optimization • Develop orchestration systems for multi-agent AI workflows • Create GPU/TPU cluster management for distributed AI processing • Implement caching strategies for billion-parameter model inference … with zero data loss • Reduce infrastructure costs by 40% through optimization • Enable 5x faster genomic pipeline execution • Successfully integrate 10+ external biological databases Integration Responsibilities Team Collaboration • Partner with LLM Engineers to optimize model serving infrastructure • Support Agentic AI Engineers with scalable agent execution platforms • Collaborate with Bioinformaticians on pipeline optimization • Work with Security teams on HIPAA-compliant implementations Platform More ❯