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For Companies At a Glance
- Tasks: Design and develop cutting-edge recommender systems and LLM-driven services.
- Company: Join an international tech lab at the forefront of applied AI research.
- Benefits: Collaborate with top universities, enjoy a dynamic work environment, and make a real impact.
- Why this job: Be part of a multi-disciplinary team focused on innovative solutions and real-world applications.
- Qualifications: 10+ years in applied ML, strong coding skills, and a PhD with notable publications.
- Other info: Expect a challenging coding test and opportunities to mentor junior researchers.
The predicted salary is between 72000 - 108000 £ per year.
An international tech lab is expanding its applied AI research centre, hiring to strengthen their work on large-scale recommender systems and LLMs powering global platforms across cloud, streaming, and mobile. This is more than a publication-first role. You’ll be joining a multi-disciplinary research centre that collaborates with top universities and industry partners, with real deployment as the end goal.
What You’ll Do:
- Design and develop production-grade recommender systems and LLM-driven services
- Run experiments on massive datasets, proposing novel approaches to real-world problems
- Present and defend your research both internally and externally
- Mentor junior researchers and guide research direction across the team
- Publish in top-tier venues, file patents, and build working prototypes
- Partner with global stakeholders to scale ideas and deliver impact
What They’re Looking For:
- 10+ years of experience in applied ML, with a strong track record in recommender systems or LLMs
- Hands-on coding skills are a must (Python, C++, R, etc.)
- PhD from a top university and multiple publications + patents all focused around LLMs
- Industry background at leading tech companies (e.g. Apple, Amazon, ByteDance)
- Ability to lead and deliver in research environments that bridge academia and industry
Process Overview:
- Coding test (challenging and mandatory, even for senior profiles)
- Research presentation (typically PhD work or a recent project)
- Deep-dive with the lab or HQ team to assess alignment
- Final HR round (salary and logistics)
Principal Researcher - LLM employer: DeepRec.ai
Contact Detail:
DeepRec.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Researcher - LLM
✨Tip Number 1
Familiarise yourself with the latest advancements in large-scale recommender systems and LLMs. This will not only help you during the coding test but also in the research presentation, as you'll be able to discuss current trends and innovations confidently.
✨Tip Number 2
Prepare to showcase your hands-on coding skills by working on relevant projects or contributing to open-source initiatives. Being able to demonstrate your proficiency in Python, C++, or R through practical examples will set you apart during the technical assessments.
✨Tip Number 3
Network with professionals in the field, especially those who have experience in bridging academia and industry. Engaging with peers can provide insights into the role and may even lead to valuable referrals or recommendations.
✨Tip Number 4
Practice presenting your research clearly and effectively. Since you'll need to defend your work, being able to communicate complex ideas simply and engagingly will be crucial during the research presentation stage.
We think you need these skills to ace Principal Researcher - LLM
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 10+ years of experience in applied ML, specifically focusing on recommender systems and LLMs. Include relevant coding skills in Python, C++, or R, and emphasise any industry experience with leading tech companies.
Craft a Strong Cover Letter: In your cover letter, express your passion for AI research and detail how your background aligns with the role. Mention specific projects or publications that demonstrate your expertise in LLMs and your ability to mentor junior researchers.
Prepare for the Coding Test: Since the coding test is mandatory, brush up on your coding skills. Practice solving complex problems in Python, C++, or R, as this will be crucial for demonstrating your hands-on abilities during the application process.
Showcase Your Research: Be ready to present your past research work, especially your PhD projects or recent contributions. Prepare a clear and engaging presentation that outlines your methodologies, findings, and the impact of your work in the field of LLMs.
How to prepare for a job interview at DeepRec.ai
✨Showcase Your Research Experience
Be prepared to discuss your past research projects in detail, especially those related to LLMs and recommender systems. Highlight any innovative approaches you've taken and the impact of your work, as this role values real-world applications.
✨Demonstrate Coding Proficiency
Since a coding test is mandatory, brush up on your skills in Python, C++, or R. Practice solving complex problems and be ready to explain your thought process during the test, as they will be looking for both skill and clarity in your coding approach.
✨Prepare for Deep-Dive Discussions
Expect to engage in detailed discussions with the lab or HQ team about your research and its alignment with their goals. Familiarise yourself with their current projects and think about how your expertise can contribute to their objectives.
✨Mentorship and Leadership Examples
As mentoring junior researchers is part of the role, come prepared with examples of how you've guided others in the past. Discuss your leadership style and how you foster collaboration within a research team, as this will demonstrate your fit for the multi-disciplinary environment.
