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For Companies At a Glance
- Tasks: Lead the design and optimisation of advanced AI models and autonomous systems.
- Company: Innovative AI firm in London with a focus on cutting-edge technology.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Other info: Exciting 12-month contract with potential for career advancement.
- Why this job: Join us to shape the future of AI and make a real impact.
- Qualifications: Experience in machine learning, AI systems, and strong engineering skills.
The predicted salary is between 60000 - 80000 £ 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 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 Remote
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and machine learning community, attend meetups, and engage on platforms like LinkedIn. 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—make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of MLOps and the latest in generative AI. Be ready to discuss your approach to building and optimising AI models, as well as how you ensure responsible AI practices.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to get noticed and ensures your application lands in the right hands. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Machine Learning Engineer - Hybrid Remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the role of a Lead Machine Learning Engineer. Highlight your expertise in LLMs, Generative AI, and MLOps to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and how your background makes you the perfect fit for leading the design and deployment of sophisticated AI models at StudySmarter.
Showcase Your Projects: Include links or descriptions of relevant projects you've worked on, especially those involving autonomous agents or advanced ML techniques. We love seeing practical applications of your skills!
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 LLM fine-tuning techniques like PEFT and LoRA, and be ready to discuss your experience with Docker, Kubernetes, and MLOps. The more specific examples you can provide, the better!
✨Showcase Your Leadership Skills
As a Lead ML Engineer, demonstrating your leadership capabilities is crucial. Prepare to share instances where you've successfully led projects or teams, especially in AI development. Highlight how you bridge the gap between data science and software engineering.
✨Prepare for Problem-Solving Questions
Expect to tackle some technical challenges during the interview. Practice explaining your thought process when designing AI algorithms or building ETL pipelines. This will show your strategic thinking and ability to optimise for scalability and performance.
✨Emphasise Responsible AI Practices
Given the focus on trustworthy and explainable AI, be prepared to discuss how you ensure fairness and compliance in your projects. Bring examples of how you've implemented metrics for bias detection or any relevant regulatory standards you've adhered to.