51 to 75 of 243 Amazon Bedrock Jobs in the UK

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

Knowledge of or experience with LLM frameworks like Haystack, LlamaIndex, and LangChain, focusing on RAG and text/chat generators. Familiarity with cloud computing on AWS (ECS, EKS, DynamoDB, Bedrock). Proficiency with git version control, branching, and code management. Commitment to code quality, performance, testing, monitoring, documentation, and CI/CD best practices. Experience working within an agile More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

of LLM frameworks such as Haystack, LlamaIndex, and LangChain, with a focus on Retrieval-Augmented Generation (RAG) and text/chat generators. Cloud computing with AWS (ECS, EKS, DynamoDB, Bedrock) Knowledge of git version control, branching, and code versioning. Passionate about code quality, adhering to best practices for code quality, performance, testing, monitoring, documentation, CI/CD. Experience working More ❯

and RLHF Inference & Acceleration: Serve models using vLLM, DeepSpeed, Triton, TensorRT Multi-Agent Orchestration: Work with LangChain, AutoGen, CrewAI, DSPy and similar tools Cloud & MLOps (AWS): Deploy with SageMaker, Bedrock, Lambda, S3, ECS, EKS Full-Stack Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Required skills & experience: 3–5+ years of experience in ML engineering and More ❯

learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and More ❯

learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and More ❯

learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and More ❯

learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and More ❯

embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB) databases Strong More ❯

multi-class classification, decision trees, support vector machines, and neural networks (deep learning experience strongly preferred) Knowledge of popular Cloud computing vendor (AWS and Azure) infrastructure & services e.g., AWS Bedrock, S3, SageMaker; Azure AI Search, OpenAI, blob storage, etc. Bachelor’s degree (master’s or higher strongly preferred) in machine learning, computer science, data science, applied mathematics or related More ❯

cloud environments. Generative AI Ecosystem Knowledge : Deep understanding of the generative AI ecosystem, including AI orchestration frameworks (e.g., LangChain, Llama Index, Haystack) and cloud provider AI offerings (e.g., AWS Bedrock, Vertex AI, Azure Machine Learning). Data Expertise : Strong foundation in data engineering, data analytics, or data science, with the ability to work effectively with various data types and More ❯

Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle, from data collection and preprocessing to model evaluation, deployment, and monitoring. More ❯

include: Deep proficiency in Python or JavaScript/TypeScript and associated AI/ML SDKs. Solid experience with cloud platforms, specifically AWS (including services like SageMaker, Lambda, S3, EC2, Bedrock). Strong software engineering fundamentals (API design, data structures, algorithms, version control with Git, testing methodologies). Understanding of full-stack application architecture and integration points. Experience working in More ❯

An understanding of AI, and AI ethics An understanding of data safety in the use of Large Language Models Knowledge and experience of either AWS or Azure: AWS (boto3, Bedrock, Sagemaker, Lambda, S3, EC2) Azure (azure Open AI service, Cosmos DB) Python Other Requirements SC cleared or 5 years uninterrupted residency in the UK and be prepared to go More ❯

embedding technologies Expert in building RAG (Retrieval-Augmented Generation) systems at scale Strong experience with MLOps practices and model deployment pipelines Proficient in cloud AI services (AWS SageMaker/Bedrock) Deep understanding of distributed systems and microservices architecture Expert in data pipeline platforms (Apache Kafka, Airflow, Spark) Proficient in both SQL (PostgreSQL, MySQL) and NoSQL (Elasticsearch, MongoDB) databases Strong More ❯