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# Machine Learning Engineer

- **Company:** Valent
- **Location:** London, UK
- **Experience:** Experienced
- **Salary:** £55,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Microsoft Azure, Big Data, C++ (Programming Language), Code Review, Data Integrity, Software Debugging, Python (Programming Language), Machine Learning, NumPy, Open Source Technology, Performance Tuning, Web Applications, Data Processing, Pytorch, Large Language Models, Multi-Agent Systems, Generative AI, Pandas, Kubernetes, HuggingFace, Machine Learning Operations, Software Version Control, Data Pipelines, Software Library, Docker
- **Published:** June 17, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=2a9528f40a381d62

## About the Role

Do you have experience in Python?, Do you have a Master's degree?, We are looking for Machine Learning Engineer with a minimum of two years expertise in Python and multimodal multi-agentic RAG., * Programming Language: Python, C++/Rust (optional)

 * ML/DL Frameworks: PyTorch (Preferred), Hugging Face (Transformers, Datasets, Tokenizers)
 * Data Processing: Pandas, NumPy

Generative AI & LLMs

 * LLM Orchestration (RAG): LangChain, LangGraph, LlamaIndex or similar
 * Vector Databases: Qdrant, FAISS, or similar
 * Fine-Tuning: Experience with fine-tuning techniques (e.g., PEFT, LoRA, QLoRA) on open-source models (e.g., Llama, Mistral), alignment-tuning (e.g. DPO, ORPO).
 * APIs: OpenAI, Anthropic, Gemini, etc.
 * Inference: vLLM, llama.cpp, SGLang, etc.

MLOps & Deployment

 * Containerization: Docker
 * Orchestration: Kubernetes (K8s) (for scalable inference)
 * Cloud Platform: AWS, GCP, or Azure (experience with S3, EC2/GCE, and a managed Kubernetes service like EKS/GKE is a strong plus)
 * Experiment Tracking: Weights & Biases (W&B) or MLflow
 * Version Control: Git / GitHub

Specialised

 * Multi-Agent Systems: AutoGen, CrewAI, LangGraph
 * Multimodal: Experience with models or techniques for handling images/video (e.g., Qwen3, Whisper, etc.)

## Description

* Develop and deploy machine learning models to enhance our disinformation detection.
 * Work with large datasets to train and validate models using Python and popular machine learning libraries.
 * Collaborate with data engineers to ensure data integrity and efficient data pipelines.
 * Integrate machine learning algorithms into existing web applications and services.
 * Participate in cross-functional teams to define, design, and ship new machine learning features.
 * Conduct code reviews and enhance the machine learning development process.
 * Troubleshoot, debug, and upgrade machine learning systems.
 * Write clean, efficient, and maintainable code while implementing security and data protection.


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