LLM Engineer – Healthcare AI (Remote, UK) in London

LLM Engineer – Healthcare AI (Remote, UK) in London

London Full-Time 63000 - 77000 Β£ / year (est.) Working from home possible
Jobgether

At a Glance

  • Tasks: Design and optimise Large Language Models for healthcare, collaborating with experts.
  • Company: Join a forward-thinking partner in the healthcare AI space.
  • Benefits: Remote work, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic role with potential for significant impact in life sciences.
  • Why this job: Make a real difference in healthcare using cutting-edge AI technology.
  • Qualifications: Experience in machine learning and familiarity with LLMs required.

The predicted salary is between 63000 - 77000 Β£ per year.

Jobgether, listing on behalf of a partner, is seeking a Machine Learning Engineer specialized in Large Language Models in the United Kingdom. You will design, optimize, and deploy LLMs for healthcare and life sciences, collaborating with ML, software, and domain experts.

You will fine-tune models, build RAG pipelines, prepare datasets, and package production-ready solutions while staying up to date with the latest ML infrastructure.

LLM Engineer – Healthcare AI (Remote, UK) in London employer: Jobgether

At Jobgether, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our remote working environment allows for flexibility while providing ample opportunities for professional growth and development in the tech industry. Join us to make a meaningful impact in enhancing open-source technology adoption, all while enjoying the benefits of a supportive team and a commitment to your career advancement.

Jobgether

Contact Details:

Jobgether Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land LLM Engineer – Healthcare AI (Remote, UK) in London

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jobgether!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like LLM Engineer – Healthcare AI (Remote, UK) at Jobgether.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jobgether.

✨Apply Directly through Our Website

When you find a suitable opening like LLM Engineer – Healthcare AI (Remote, UK) at Jobgether, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace LLM Engineer – Healthcare AI (Remote, UK) in London

Machine Learning
Large Language Models (LLMs)
Model Fine-Tuning
RAG Pipelines
Dataset Preparation
Production-Ready Solutions
Collaboration with Domain Experts

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Jobgether, 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 Jobgether. 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 Jobgether

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨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 Jobgether!

✨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.