Machine Learning Engineer
Posted 1 week ago by Randstad Digital
Negotiable
Undetermined
Hybrid
London Area, United Kingdom
Summary: The Lead Machine Learning Engineer role focuses on designing, deploying, and optimizing advanced AI models and Agentic Systems, with an emphasis on building autonomous agents. The position requires hands-on leadership in AI, particularly in LLM fine-tuning and MLOps. The role is based in London and involves a hybrid working arrangement, requiring in-office presence two days a week. This is a 12-month contract position aimed at developing intelligent AI systems that are trustworthy and efficient.
Key Responsibilities:
- Design and implement AI algorithms and architectures.
- Develop intelligent AI agents capable of reasoning and planning.
- Handle LLM fine-tuning and RAG pipelines.
- Build ETL/ELT pipelines and feature engineering workflows.
- Own the end-to-end MLOps lifecycle, including CI/CD automation and containerization.
- Ensure responsible AI practices, focusing on trustworthiness, fairness, and explainability.
Key Skills:
- Expertise in LLMs, Generative AI, and Agentic workflows.
- Proficiency in PEFT, Vector Databases, and Prompt Engineering.
- Experience with Docker, Kubernetes, and CI/CD processes.
- Knowledge of ETL/ELT processes and Feature Stores.
- Strong documentation and data governance skills.
- Strategic thinking for scalability and cost-efficiency.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: hybrid
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Lead Machine Learning Engineer (Generative AI & Agentic Systems)
Location: London, UK (Hybrid: 2 days/week in-office)
Type: 12-Month Contract
The Opportunity
Are you a hands-on leader in the AI space? We are looking for a Lead ML Engineer to spearhead the design, deployment, and optimization of sophisticated AI models and Agentic Systems . This isn't just about standard predictive modeling—you’ll be building autonomous agents that reason and execute, leveraging the latest in LLM fine-tuning, RAG pipelines, and scalable MLOps.
The Core Mission
- Architect & Build: Design and implement AI algorithms and architectures, moving from raw concepts to robust frameworks.
- Agentic Systems & LLMs: Develop intelligent AI agents capable of reasoning and planning. Expertly handle LLM fine-tuning (PEFT, LoRA, QLoRA) and RAG pipelines.
- Data Orchestration: Build ETL/ELT pipelines and feature engineering workflows to integrate structured and unstructured data into centralized platforms.
- End-to-End MLOps: Own the lifecycle—from CI/CD automation and containerization (Docker/Kubernetes) to versioning and infrastructure management.
- Responsible AI: Ensure every system is trustworthy, fair, and explainable, implementing quantifiable metrics for bias detection and regulatory compliance.
Technical Toolkit
- Models: LLMs, Generative AI, Agentic workflows.
- Engineering: PEFT, Vector Databases (Pinecone/Milvus/Weaviate), Prompt Engineering.
- Ops: Docker, Kubernetes, CI/CD, Experiment Tracking (MLflow/W&B).
- Data: ETL/ELT, Feature Stores, Performance Tuning.
Who You Are
- A Technical Lead: You can bridge the gap between Data Science, Software Engineering, and the business.
- A Precision Engineer: You value documentation, data governance, and "bulletproof" deployment.
- A Strategic Thinker: You don’t just build; you optimize for scalability, performance, and cost-efficiency.
Logistics
- Contract: 12-month initial term.
- Location: London-based office.
- Candidates must be able to commute to the office 2 days per week (mandatory).
Are you ready to build the next generation of autonomous AI?