At a Glance
- Tasks: Design and deploy cutting-edge machine learning models for revolutionary medical AIs.
- Company: Scarlet, a leading AI medical device certifier transforming healthcare.
- Benefits: Competitive salary, equity options, and the chance to impact global healthcare.
- Other info: Join a rapidly growing team with excellent career advancement opportunities.
- Why this job: Make a real difference in accessible healthcare while working with top AI experts.
- Qualifications: 3+ years in machine learning with a passion for building innovative solutions.
The predicted salary is between 90000 - 150000 £ per year.
As a Machine Learning Engineer at Scarlet, you will deploy state-of-the-art models and build distributed agentic systems to accelerate market access for groundbreaking medical AIs. You will fine-tune LLMs and create exceptional datasets, directly impacting universally accessible healthcare by ensuring innovative technology reaches patients safely and quickly. Join a team with product-market fit and exponential growth.
Location: London, UK
Why this role is remarkable:
- Directly contribute to universally accessible healthcare by certifying groundbreaking medical AIs safely and quickly.
- Join a team with strong product-market fit, flowing data, and exponentially growing revenue as the pre-eminent authority in its field.
- Work with the brightest minds in AI medical devices, deploying state-of-the-art models and building distributed agentic systems.
What you will do:
- Design and deploy concurrent agent architectures for rapid, multi-agent evidence gathering from diverse customer data sources.
- Develop and implement robust evaluation systems, leveraging production workflows to ensure accurate certification timelines.
- Fine-tune LLMs and orchestrate agent swarms to create high-quality datasets and align AI systems with strict regulatory standards.
The ideal candidate:
- Possess 3+ years of experience shipping production-grade machine learning software.
- Proven ability to create high-quality datasets and establish robust, reality-aligned ML evaluation systems.
- A “hacker” and “builder” mindset, taking ambitious projects from concept to reality with a focus on economic and human value.
How to Apply:
To apply for this job, speak to Jack, our AI recruiter.
- Visit our website
- Click 'Speak with Jack'.
- Login with your LinkedIn profile.
- Talk to Jack for 20 minutes so he can understand your experience and ambitions.
- If the hiring manager would like to meet you, Jack will make the introduction.
Machine Learning Engineer (£90k-£150k + Equity) at Scarlet employer: Jack & Jill/External Ats
Scarlet is an exceptional employer, offering a unique opportunity to work at the forefront of AI in healthcare. With a strong focus on employee growth and innovation, team members are encouraged to collaborate with leading experts while contributing to meaningful advancements in universally accessible healthcare. Located in London, employees benefit from a vibrant work culture that fosters creativity and ambition, alongside competitive salaries and equity options.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer (£90k-£150k + Equity) at Scarlet
✨Tip Number 1
Make sure you know your stuff! Brush up on the latest trends in machine learning and AI. When you chat with Jack, show off your knowledge and passion for the field – it’ll definitely make you stand out!
✨Tip Number 2
Don’t just focus on your technical skills; be ready to discuss how your work can impact healthcare. Think about examples where your projects have made a difference, and share those stories with Jack.
✨Tip Number 3
Networking is key! Connect with others in the industry, attend meetups, or join online forums. The more people you know, the better your chances of landing that dream job at Scarlet.
✨Tip Number 4
Remember, applying through our website is the way to go! It’s super easy – just click 'Speak with Jack' and let him guide you through the process. He’s got your back!
We think you need these skills to ace Machine Learning Engineer (£90k-£150k + Equity) at Scarlet
Some tips for your application 🫡
Show Off Your Skills:When you're writing your application, make sure to highlight your experience with machine learning and any cool projects you've worked on. We want to see how you can bring your skills to the table at Scarlet!
Tailor Your Application:Don’t just send a generic application! Take a moment to tailor your CV and cover letter to match the job description. We love seeing candidates who understand what we’re looking for and how they fit into our mission.
Be Authentic:Let your personality shine through in your application. We’re not just looking for qualifications; we want to know who you are and what drives you. Share your passion for AI and healthcare!
Follow the Steps:Make sure to follow the application steps on our website. Speak with Jack, our AI recruiter, as he’s here to help you navigate the process and ensure you get noticed for this exciting role!
How to prepare for a job interview at Jack & Jill/External Ats
✨Know Your Stuff
Make sure you brush up on the latest trends in machine learning and AI, especially as they relate to medical devices. Be ready to discuss your past projects and how they align with what Scarlet is doing. This shows you're not just a candidate, but someone who genuinely cares about the field.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Scarlet is looking for a 'hacker' and 'builder' mindset, so highlight your ability to take ambitious projects from concept to reality. Use examples that demonstrate your creativity and technical prowess.
✨Understand the Company’s Mission
Familiarise yourself with Scarlet's mission to make healthcare universally accessible through innovative technology. Be prepared to discuss how your skills can contribute to this goal. Showing that you resonate with their vision will set you apart from other candidates.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions. Inquire about the team dynamics, the technologies they use, or their future projects. This not only shows your interest but also helps you gauge if Scarlet is the right fit for you.
