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For Companies At a Glance
- Tasks: Lead the design and deployment of cutting-edge AI models and autonomous agents.
- Company: Innovative AI company based in London with a focus on generative technologies.
- Benefits: Competitive contract salary, hybrid work model, and opportunities for professional growth.
- Other info: Exciting 12-month contract with potential for career advancement in a dynamic environment.
- Why this job: Join a pioneering team to shape the future of AI and make a real impact.
- Qualifications: Experience in machine learning, AI algorithms, and strong engineering skills required.
The predicted salary is between 70000 - 90000 £ per year.
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?
Machine Learning Engineer (hybrid or remote) employer: Randstad Digital
Contact Detail:
Randstad Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer (hybrid or remote)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning community on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and agentic systems. This is your chance to demonstrate your hands-on experience and technical prowess.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of MLOps and data orchestration. Be ready to discuss how you've tackled challenges in previous roles, especially around CI/CD and containerization.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer (hybrid or remote)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Machine Learning Engineer role. Highlight your expertise in AI, LLMs, and MLOps to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how your background makes you the perfect fit for this position. Be genuine and let your personality shine through!
Showcase Your Projects: If you've worked on relevant projects, whether personal or professional, make sure to mention them. We love seeing practical applications of your skills, especially in generative AI and agentic systems.
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures it reaches the right people quickly!
How to prepare for a job interview at Randstad Digital
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical toolkit mentioned in the job description. Brush up on LLMs, Generative AI, and MLOps tools like Docker and Kubernetes. Be ready to discuss your hands-on experience with these technologies and how you've applied them in real-world scenarios.
✨Showcase Your Leadership Skills
As a Lead ML Engineer, demonstrating your leadership capabilities is crucial. Prepare examples of how you've led projects or teams in the past, especially in AI development. Highlight your ability to bridge gaps between data science and software engineering, showcasing your strategic thinking.
✨Prepare for Problem-Solving Questions
Expect to face technical challenges during the interview. Practice solving problems related to AI algorithms, data orchestration, and MLOps. Think through your approach to building autonomous agents and optimising systems for scalability and performance, as these are key aspects of the role.
✨Understand Responsible AI Principles
Familiarise yourself with concepts around responsible AI, including fairness, explainability, and bias detection. Be prepared to discuss how you would implement these principles in your work, ensuring that the systems you build are trustworthy and compliant with regulations.