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- Tasks: Join a team to build and scale AI infrastructure for global health applications.
- Company: Leading consumer healthtech platform with a unicorn valuation.
- Benefits: Competitive salary, remote work options, and career growth opportunities.
- Why this job: Impact the health of over 70 million users with cutting-edge AI technology.
- Qualifications: 4+ years in AI/ML systems, proficient in Python and modern ML tools.
- Other info: Dynamic environment with a focus on privacy-first AI initiatives.
The predicted salary is between 28800 - 48000 £ per year.
Global consumer healthtech platform.
You will join a specialized AI Platform team to build and scale shared infrastructure enabling safe, efficient AI integration across a massive global product. The role involves fine-tuning large language models, optimizing MLOps pipelines, and developing evaluation frameworks to ensure medical safety and high performance for over 70 million monthly users worldwide.
Location: London, UK
Why this role is remarkable:
- Work on a product with over 500 million downloads, directly impacting the health and wellness of a massive global user base.
- Join a unicorn-valuation organization backed by top-tier global private equity and venture capital firms.
- Lead the transition into a privacy-first, AI-powered future by building the central infrastructure that powers every product team's AI initiatives.
Responsibilities:
- Develop, fine-tune, and optimize proprietary and open-source large language models for domain-specific health applications.
- Design and maintain automated pipelines for model training, evaluation, and deployment across diverse AI workloads.
- Build LLM evaluation frameworks to measure model safety, medical accuracy, and overall performance at scale.
Ideal Candidate:
- Has 4+ years of professional experience building and deploying production-grade AI/ML systems within a cloud environment.
- Possesses deep engineering experience with LLM infrastructure, including fine-tuning techniques like LoRA and SFT.
- Is proficient in Python and modern ML tools such as Databricks, MLflow, and experiment tracking systems.
AI/ML Engineer in London employer: Jack & Jill
Contact Detail:
Jack & Jill Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Engineer in London
✨Tip Number 1
Get to know the company inside out! Research their products, values, and recent news. This will help you tailor your conversations and show genuine interest when you chat with Jack.
✨Tip Number 2
Practice makes perfect! Prepare for potential interview questions related to AI/ML systems and be ready to discuss your experience with LLMs and MLOps pipelines. The more you rehearse, the more confident you'll feel.
✨Tip Number 3
Network like a pro! Connect with professionals in the healthtech and AI space on platforms like LinkedIn. You never know who might have insights or opportunities that could lead you to your dream job.
✨Tip Number 4
Don't forget to apply through our website! By talking to Jack, you’ll get personalised support and access to roles that might not be advertised elsewhere. Plus, it’s all free!
We think you need these skills to ace AI/ML Engineer in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with AI/ML systems and any specific projects you've worked on. We want to see how you’ve fine-tuned models or optimised pipelines, so don’t hold back!
Tailor Your Application: Customise your application to match the job description. Use keywords from the role, like 'large language models' and 'MLOps', to show us you’re a perfect fit for the team.
Be Clear and Concise: Keep your application straightforward and to the point. We appreciate clarity, so make sure your experience and skills shine through without unnecessary fluff.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to connect with you and ensure your application gets into the right hands. Plus, Jack is ready to help you out!
How to prepare for a job interview at Jack & Jill
✨Know Your Models Inside Out
Make sure you’re well-versed in the large language models relevant to the role. Brush up on fine-tuning techniques like LoRA and SFT, and be ready to discuss how you've applied these in your previous work. This will show that you not only understand the theory but also have practical experience.
✨Showcase Your MLOps Skills
Prepare to talk about your experience with MLOps pipelines. Be specific about the tools you've used, such as Databricks and MLflow, and how you've designed automated processes for model training and deployment. Real-world examples will help you stand out.
✨Emphasise Safety and Accuracy
Given the focus on medical safety and performance, be ready to discuss how you’ve built evaluation frameworks in the past. Highlight any metrics or methodologies you’ve used to ensure model accuracy and safety, especially in health applications.
✨Be Ready for Technical Questions
Expect some technical questions during the interview. Brush up on your Python skills and be prepared to solve problems on the spot. Practising coding challenges related to AI/ML can give you a confidence boost and help you think on your feet.
