1 to 25 of 310 LLM Jobs in the South East

are proficient in developing data pipelines for large, complex datasets using Python, SQL, NoSQL, and big data tools, preferably on AWS or Azure. You have hands-on experience with LLM operations and agentic AI tools such as GPT-5, LangChain, and vector databases. You understand MLOps, including deployment, monitoring, and CI/CD pipelines, and can effectively communicate complex technical More ❯

include engaging in discussions with customers and understanding their generative AI needs and using platform tools and packages to finetune and iterate on modeling experiments using Large Language Models (LLM) or Retrieval Augmented Generation (RAG). Your experiments should be focused around data and metrics that drive continuous improvement. This includes designing data-driven experiments focused on optimizing model performance More ❯

Azure/GCP), CI/CD, Docker/Kubernetes; workflow orchestration (Airflow/Prefect); experiment tracking (MLflow/W&B). Machine Learning for time series/tabular data; LLM/agentic systems, retrieval pipelines, and evaluation/guardrails. Research driven, rigorous and curious; clear scientific writing with a publication mindset. Ability to communicate complex ideas to non-technical audiences More ❯

are looking for: Research engineering: 5+ years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

are looking for: Research engineering: 5+ years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

are looking for: Research engineering: 5+ years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product features. Stay up More ❯

experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product features. Stay up More ❯

experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and communicate results across cross-functional teams. Define, implement, and monitor key performance metrics for AI-driven product features. Stay up More ❯

contextual AI assistance in day-to-day engineering workflows. Exposure to incorporating LLMs into engineering workflows for production-ready applications, including prompt engineering and context management. Familiarity with multiple LLM providers (e.g. OpenAI, Anthropic, Google) and an understanding of their comparative strengths, trade-offs, and integration models. Experience with AI/ML toolchains such as OpenAI, Hugging Face, LangChain, or More ❯

Ensure your agents comply with regulations (GDPR, financial compliance) and guard against bias, hallucinations, and misuse. What You Bring Technical Mastery: Strong skills in Python, JavaScript, or similar languages. LLM & Agent Expertise: Hands-on experience with LLMs (OpenAI, Anthropic, Mistral) and agent frameworks. Advanced Tools: Familiarity with vector databases, RAG pipelines, prompt engineering, REST APIs, cloud deployment, and containerization (Docker More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

of API design, data modelling, and microservice architecture. Excellent communication skills, with the ability to translate technical outcomes into business impact. Tech Environment Languages: Python, TypeScript, Java AI/LLM: OpenAI, Anthropic, Retrieval-Augmented Generation (RAG) Infrastructure: AWS (Lambda, ECS, S3), Terraform, Docker Databases: PostgreSQL, MySQL, Redis, vector databases DevOps: GitHub, CI/CD pipelines Why Join Competitive salary and More ❯

and retraining pipelines. Exposure to feature stores, registries, and experimentation frameworks. Familiarity with business-driven metrics and experience balancing ML performance with commercial goals. Experience with generative AI and LLM frameworks for fine tuning, evaluation, deployment and serving desirable. About Rightmove Our vision is to give everyone the belief they can make their move. We aim to make moving simpler More ❯

and retraining pipelines. Exposure to feature stores, registries, and experimentation frameworks. Familiarity with business-driven metrics and experience balancing ML performance with commercial goals. Experience with generative AI and LLM frameworks for fine tuning, evaluation, deployment and serving desirable. About Rightmove Our vision is to give everyone the belief they can make their move. We aim to make moving simpler More ❯

the company. What we are looking for: Research engineering: Industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying More ❯

the company. What we are looking for: Research engineering: Industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying More ❯

the company. What we are looking for: Research engineering: Industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying More ❯

technical discovery or architecture definition in a scaling SaaS or fintech environment. Familiarity with event-driven or streaming architectures (Kafka, Apache Flink, etc.). Practical exposure to AI/LLM orchestration frameworks or fine-tuning workflows. Experience designing developer tools, data platforms, or intelligent systems. Interest in or experience mentoring engineers in applied AI. Degree in Computer Science or related More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

looking for: Research engineering: 2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers More ❯

Key Responsibilities Design, build, and deploy Python-based AI and ML applications . Research and develop new Generative AI techniques, including fine-tuning and prompt engineering. Develop and maintain LLM-assisted frameworks and automation pipelines. Write clean, maintainable, and well-documented code for scalable deployment. Build and implement testing and evaluation frameworks for AI models. Collaborate with data scientists, software More ❯

exhibits good interpersonal skills. Able to prioritise, multi-task, and deliver at pace with an iterative mindset. Experience with modern data platforms such as Databricks or Snowflake is advantageous; LLM API experience is a bonus. What’s in it for you?: Competitive salary that reflects your skills, experience and potential. Discretionary bonus scheme that recognises your hard work and contributions More ❯