London, South East, England, United Kingdom Hybrid / WFH Options
IT Graduate Recruitment
publish. What We’re Looking For 0–3 years of experience in Machine Learning, Data Science, or NLP/LLM. Strong Python skills; exposure to PyTorch/TensorFlow/Hugging Face. (Bonus) understand fundamentals of deep learning, LLMs, and MLOps, vector databases, embeddings, or retrieval-augmented generation (RAG). Loves solving complex problems and thrives in a fast-moving … Get Hands-on mentorship from senior ML engineers, AI researchers, and founders. Freedom to experiment with state-of-the-art models, tools, and frameworks. Modern tech stack (Python, LangChain, HuggingFace, OpenAI API, Pinecone, Kubernetes, etc.). Flexible working — remote-first culture with in-person team sessions for collaboration. Career acceleration — opportunities to own projects, lead development, and … genuinely moves the needle. Machine Learning Engineer, LLM Engineer, AI Engineer, Artificial Intelligence, Deep Learning, NLP, Natural Language Processing, Large Language Models, Generative AI, GenAI, Neural Networks, PyTorch, TensorFlow, HuggingFace, OpenAI, LangChain, RAG, Retrieval-Augmented Generation, Python, Data Science, AI Research, MLOps, Data Pipelines, Prompt Engineering, Model Fine-Tuning, Cloud Computing, AWS, Azure, Google Cloud, AI Infrastructure More ❯
deployed through a fully automated AWS environment (Terraform, Ansible, GitHub Actions). Alongside this, we're building the next generation of our data and AI infrastructure - exploring frameworks like HuggingFace, LangChain, LlamaIndex and agent orchestration systems. We use Cursor and Copilot to speed iteration and experimentation. We're always open to new approaches, whether it's a … message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, HuggingFace, LangChain). Experience working with AI-driven development tools such as Cursor, Copilot, or Replit Ghostwriter. Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Interest More ❯
london, south east england, united kingdom Hybrid / WFH Options
BondAval
deployed through a fully automated AWS environment (Terraform, Ansible, GitHub Actions). Alongside this, we're building the next generation of our data and AI infrastructure — exploring frameworks like HuggingFace, LangChain, LlamaIndex and agent orchestration systems. We use Cursor and Copilot to speed iteration and experimentation. We're always open to new approaches, whether it's a … balance speed, security, and reliability in a growing platform. You're passionate about AI and LLMs — from using tools like Cursor and Copilot to experimenting with frameworks such as HuggingFace or LangChain. You communicate clearly, collaborate across disciplines, and translate technical complexity into business context. You enjoy guiding direction while staying hands-on when needed. Nice to More ❯
tool use, memory and hand-offs; build resilient multi-agent journeys for discovery → advice → purchase. LLM training & tuning: Run LoRA/QLoRA/full fine-tunes with PyTorch/HuggingFace on Vertex AI ; own data curation and the evaluation harness. Measurement: Set and track KPIs (task completion, hand-off success, latency/cost/factuality, business outcomes … Classical ML where it counts: Ship intent classifiers, outcome forecasters and recommendation pipelines with scikit-learn/XGBoost/LightGBM . Stack (core) Python (production-grade) LLM tooling: PyTorch, HuggingFace, TensorFlow Fine-tuning: LoRA/QLoRA/full training GCP/Vertex AI: Training, Pipelines, Registry/Deploy Experimentation: SQL, A/B test design, causal thinking More ❯
Proven experience in building AI/ML systems, ideally with Azure OpenAI, Azure Cognitive Services Azure Machine Learning. Strong Python skills and familiarity with modern AI frameworks (e.g., LangChain, HuggingFace, PyTorch). Deep understanding of LLMs, vector databases, prompt engineering, and multi-agent systems. Passion for building from scratch - you thrive in greenfield environments. Based in or … creative freedom. Hybrid flexibility with a vibrant London office. Competitive salary, equity options, and a culture of innovation. Strong Python skills and familiarity with modern AI frameworks (e.g., LangChain, HuggingFace, PyTorch). Deep understanding of LLMs, vector databases, prompt engineering, and multi-agent systems. Passion for building from scratch - you thrive in greenfield environments. Based in London More ❯
Proven experience in building AI/ML systems, ideally with Azure OpenAI, Azure Cognitive Services Azure Machine Learning. Strong Python skills and familiarity with modern AI frameworks (e.g., LangChain, HuggingFace, PyTorch). Deep understanding of LLMs, vector databases, prompt engineering, and multi-agent systems. Passion for building from scratch - you thrive in greenfield environments. Based in or … creative freedom. Hybrid flexibility with a vibrant London office. Competitive salary, equity options, and a culture of innovation. Strong Python skills and familiarity with modern AI frameworks (e.g., LangChain, HuggingFace, PyTorch). Deep understanding of LLMs, vector databases, prompt engineering, and multi-agent systems. Passion for building from scratch - you thrive in greenfield environments. Based in London More ❯
South East London, London, United Kingdom Hybrid / WFH Options
Profile 29
MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, HuggingFace) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving … at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain HuggingFace LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Profile 29
MSc or equivalent experience) Hands-on experience building and deploying Agentic AI or multi-agent systems Proficiency in Python and popular AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, HuggingFace) Familiarity with LLM fine-tuning, reasoning, and retrieval-augmented generation (RAG) techniques Experience integrating AI models into production systems or orchestration platforms Strong analytical and problem-solving … at least the next 5 years. Profile 29 recruitment keywords: Artificial intelligence large language models AI machine learning Agentic AI multi-agent Python AI/ML PyTorch TensorFlow LangChain HuggingFace LLM retrieval augmented generation RAG AI models orchestration platforms Public sector SC Security Clearance agent architectures ReAct AutoGen CrewAI BabyAGI reasoning loops memory systems governance frameworks public More ❯
Newbury, Berkshire, United Kingdom Hybrid / WFH Options
Viavi
field (Master's a plus) Extensive experience in professional software development Strong Python skills and a track record of delivering maintainable, well-tested code Experience with LLM APIs (OpenAI, HuggingFace, Anthropic) or ML frameworks (PyTorch, TensorFlow) Solid understanding of CI/CD, Git, testing, and agile methodologies Hands-on experience with Linux, Docker, and containerized deployments Familiarity More ❯
in SQL/NoSQL databases and API development/integration. Proven ability to analyze model performance and optimize for accuracy, efficiency, and scalability. Exposure to prominent AI frameworks like HuggingFace, LangChain. Preferred/Advantage - Understanding of data structures, algorithms, and solution architecture. Familiarity with major cloud AI platforms (AWS, Azure, GCP). Broad knowledge of various ML More ❯
Copilot, Cursor, and Codeium to 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. More ❯
Strong experience in AI engineering or ML backend development , with a foundation in data engineering and MLOps . Expert-level proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow, HuggingFace). Practical experience with MLOps principles , including CI/CD for ML, monitoring, and deployment. Strong understanding of LLMs, NLP , and modern data infrastructure. Familiarity with cloud More ❯
Perplexity. Strong understanding of generative AI principles, prompt chaining, context window management, and token efficiency. Proficiency in Python and experience with AI/ML frameworks like TensorFlow, PyTorch, or Hugging Face. Experience integrating AI into enterprise platforms such as DealCloud, Salesforce, or similar CRMs. Understanding of workflow automation tools (e.g., Zapier, n8n, Make) and dashboarding platforms (e.g., Power BI More ❯
Description: Strong programming skills 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 HuggingFace 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/ More ❯
Description: Strong programming skills 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 HuggingFace 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/ More ❯
Description: Strong programming skills 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 HuggingFace 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/ More ❯
Description: Strong programming skills 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 HuggingFace 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/ More ❯
london (city of london), south east england, united kingdom
Luxoft
Description: Strong programming skills 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 HuggingFace 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/ More ❯
Cambridge, England, United Kingdom Hybrid / WFH Options
Neutreeno
foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, HuggingFace, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating across More ❯
cambridge, east anglia, united kingdom Hybrid / WFH Options
Neutreeno
foundational understanding and subsequent practical application of ML techniques, preferably NLPs, LLMs, Bayesian Optimisation and MCMCs Strong proficiency in Python and ML frameworks and tools (e.g. PyTorch, TensorFlow, JAX, HuggingFace, vLLM, MCP, prompt engineering) Excellent communication skills and ability to explain ML concepts to non-technical stakeholders Ability to work effectively in multi-disciplinary teams, collaborating across More ❯
or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML platforms, pipelines, and tooling in cloud environments (e.g., AWS, GCP, Azure). Preferred: PhD or MS More ❯
or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML platforms, pipelines, and tooling in cloud environments (e.g., AWS, GCP, Azure). Preferred: PhD or MS More ❯
or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML platforms, pipelines, and tooling in cloud environments (e.g., AWS, GCP, Azure). Preferred: PhD or MS More ❯
or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML platforms, pipelines, and tooling in cloud environments (e.g., AWS, GCP, Azure). Preferred: PhD or MS More ❯
london (city of london), south east england, united kingdom
oryxsearch.io
or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML platforms, pipelines, and tooling in cloud environments (e.g., AWS, GCP, Azure). Preferred: PhD or MS More ❯