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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 in London with a focus on generative AI and agentic systems.
- Benefits: Competitive contract salary, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic work environment with a strong emphasis on responsible AI practices.
- Why this job: Join a pioneering team to shape the future of AI technology and make a real impact.
- Qualifications: Experience in machine learning, AI algorithms, and MLOps 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 employer: Randstad Digital
Contact Detail:
Randstad Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and machine learning community. Attend meetups, webinars, or conferences—these are golden opportunities to meet potential employers and learn about job openings before they hit the market.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and generative AI. Share your work on platforms like GitHub or even your own website. This gives hiring managers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with MLOps, Docker, and Kubernetes. Practice common interview questions and have examples ready that demonstrate your problem-solving abilities and strategic thinking.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role and highlighting your relevant experience.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Lead Machine Learning Engineer. Highlight your experience with LLMs, generative AI, and any relevant projects that showcase your skills in building autonomous agents.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you the perfect fit for this role. Don’t forget to mention your hands-on leadership experience!
Showcase Your Technical Skills: Be specific about the tools and technologies you’ve worked with, like Docker, Kubernetes, and MLflow. We want to see your expertise in action, so include examples of how you've used these in past projects.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
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 LLM fine-tuning techniques like PEFT and LoRA, and be ready to discuss your experience with Docker, Kubernetes, and CI/CD processes. The more confident you are in these areas, the better you'll impress the interviewers.
✨Showcase Your Projects
Prepare to talk about specific projects where you've designed and implemented AI algorithms or built autonomous agents. Highlight your role in the project, the challenges you faced, and how you overcame them. Real-world examples will demonstrate your hands-on experience and problem-solving skills.
✨Understand Responsible AI
Familiarise yourself with concepts of responsible AI, including fairness, explainability, and bias detection. Be ready to discuss how you’ve ensured compliance and trustworthiness in your previous work. This shows that you not only build systems but also care about their impact.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s approach to AI and their expectations for the role. Inquire about their current projects or challenges they face in deploying agentic systems. This not only shows your interest but also helps you gauge if the company aligns with your values and career goals.