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- Tasks: Build and deploy ML models using LLMs and evaluate their effectiveness.
- Company: Join a dynamic startup revolutionising access to performance coaching through innovative tech.
- Benefits: Be part of a growing team with opportunities for remote work and exciting corporate perks.
- Why this job: Work at the forefront of AI technology in a culture that values innovation and impact.
- Qualifications: 5+ years in ML engineering, strong programming skills, and cloud experience required.
- Other info: Ideal candidates will have a passion for LLMs and knowledge graphs.
The predicted salary is between 54000 - 84000 £ per year.
Our client is a startup providing tech to give regular people access to services previously reserved for top executives or athletes - Performance Coaching. The app has a waiting list!
The product is built AI first, and they are continuing to push the effectiveness of AI within their product, and this will be through using LLM's and Computer Vision.
The correct candidate will have a good understanding of LLM’s and RAG, and more importantly know how to measure and evaluate LLM's.
What it offers:- The opportunity to build and deploy ML Models utilising LLM's.
- Join a startup at the most exciting time of growth, and the chance to focus on the product outcomes.
- 5+ years experience in an ML focused Engineering position.
- Solid programming skills and Cloud experience (Ideally Google Cloud or Azure).
- A keen interest in utilising LLM's.
- Ideally, professional experience with Knowledge Graphs.
Contact Detail:
Few&Far Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network with professionals in the AI and machine learning community. Attend meetups, webinars, or conferences where you can connect with others who work in similar fields. This can help you learn about the latest trends and potentially get referrals for job openings.
✨Tip Number 2
Showcase your expertise in LLMs and RAG through personal projects or contributions to open-source initiatives. Having tangible examples of your work can set you apart from other candidates and demonstrate your hands-on experience.
✨Tip Number 3
Prepare to discuss how you measure and evaluate LLMs during interviews. Be ready to share specific metrics or methodologies you've used in past projects, as this will highlight your understanding and practical experience in the field.
✨Tip Number 4
Familiarise yourself with the startup's product and its unique selling points. Understanding their approach to performance coaching and how AI plays a role will allow you to tailor your discussions and show genuine interest in their mission.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning, particularly with LLMs and RAG. Include specific projects or roles where you've successfully built and deployed ML models.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the startup environment and how your skills align with their mission. Mention your programming skills and cloud experience, and provide examples of how you've used LLMs in previous roles.
Showcase Relevant Projects: If you have worked on projects involving computer vision or knowledge graphs, be sure to include these in your application. Describe your role and the impact of your contributions to demonstrate your expertise.
Highlight Continuous Learning: Mention any recent courses, certifications, or workshops related to AI and machine learning that you've completed. This shows your commitment to staying updated in a rapidly evolving field.
How to prepare for a job interview at Few&Far
✨Showcase Your Technical Skills
Be prepared to discuss your experience with LLMs and RAG in detail. Bring examples of projects where you've successfully implemented these technologies, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Your Problem-Solving Ability
Expect to face technical questions that assess your problem-solving skills. Think through your approach to measuring and evaluating LLMs, and be ready to share your thought process during the interview.
✨Highlight Your Cloud Experience
Since the role requires cloud experience, make sure to discuss your familiarity with Google Cloud or Azure. Share specific instances where you've deployed ML models in a cloud environment and the impact it had on the project.
✨Express Your Passion for AI and Startups
Convey your enthusiasm for working in a startup environment and your interest in AI technologies. Discuss why you are excited about the potential of performance coaching and how you see your role contributing to the company's growth.
