Senior ML Engineer: Healthcare AI & Agentic LLM Systems

Senior ML Engineer: Healthcare AI & Agentic LLM Systems

Full-Time 81000 - 99000 £ / year (est.) No working from home possible
Latitude

At a Glance

  • Tasks: Lead ML projects in healthcare, creating reliable AI systems from data prep to deployment.
  • Company: Latitude, a forward-thinking company revolutionising healthcare with AI.
  • Benefits: Attractive salary, health perks, flexible working, and opportunities for growth.
  • Other info: Join a dynamic team with a focus on innovation and mentorship.
  • Why this job: Make a real difference in healthcare by building impactful AI solutions.
  • Qualifications: Experience in machine learning and strong collaboration skills required.

The predicted salary is between 81000 - 99000 £ per year.

Latitude in the United Kingdom seeks a Senior ML Engineer to own end-to-end ML initiatives in a high-impact healthcare environment, building production-grade AI systems with reliability and safety at the core.

You will work across the AI stack from data preparation to serving, designing agentic LLMs with tool use, retrieval, and orchestration, and mentoring engineers while collaborating with Product, Clinical, and Engineering teams.

Senior ML Engineer: Healthcare AI & Agentic LLM Systems employer: Latitude

Brunswick is an exceptional employer that fosters a culture of inclusivity, excellence, and intellectual curiosity, making it an ideal place for an AI Engineer to thrive. With a commitment to employee growth, Brunswick offers comprehensive benefits, continuous professional development opportunities, and the chance to work alongside talented professionals in a dynamic global environment. The AI Lab serves as a pioneering hub for innovation, ensuring that employees are equipped with cutting-edge tools and skills to deliver impactful solutions while enjoying a collaborative and supportive workplace.

Latitude

Contact Details:

Latitude Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior ML Engineer: Healthcare AI & Agentic LLM Systems

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Apply Directly through Our Website

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We think you need these skills to ace Senior ML Engineer: Healthcare AI & Agentic LLM Systems

Machine Learning
AI Systems Development
Data Preparation
Production-Grade System Design
Agentic LLMs
Tool Use and Retrieval
Orchestration

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

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Craft a Tailored Cover Letter:For a full-time role at Latitude, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Latitude. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Latitude

Brush Up on Your Statistics

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Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Latitude!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.