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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: Enjoy a collaborative environment with opportunities for mentorship and innovation.
- Why this job: Make a real impact by solving complex problems and collaborating with top-tier partners.
- Qualifications: 10+ years in applied ML, strong coding skills, and a PhD with notable publications.
- Other info: Expect a challenging coding test and engaging research presentations as part of the hiring process.
The predicted salary is between 57600 - 96000 £ 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)
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. Being well-versed in current trends and breakthroughs will not only help you during the coding test but also in discussions with the team about your research ideas.
✨Tip Number 2
Prepare to showcase your hands-on coding skills by working on relevant projects or contributing to open-source initiatives. This practical experience will be invaluable during the coding test and will demonstrate your ability to apply theoretical knowledge in real-world scenarios.
✨Tip Number 3
Practice presenting your research clearly and confidently. Since you'll need to defend your work, rehearsing your presentation skills can make a significant difference in how effectively you communicate your ideas and findings.
✨Tip Number 4
Network with professionals in the field, especially those who have experience in bridging academia and industry. Engaging with others can provide insights into the role and may even lead to valuable connections that could support your application.
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 and any industry experience at leading tech companies.
Craft a Strong Cover Letter: In your cover letter, emphasise your hands-on coding skills and your ability to bridge academia and industry. Mention specific projects or publications that demonstrate your expertise in LLMs and your experience mentoring junior researchers.
Prepare for the Coding Test: Since the coding test is mandatory, brush up on your programming skills in Python, C++, or R. Practice solving complex problems and be ready to showcase your coding abilities during the application process.
Research Presentation: Prepare a compelling research presentation based on your PhD work or a recent project. Focus on how your research aligns with the company's goals and be ready to defend your ideas confidently.
How to prepare for a job interview at DeepRec.ai
✨Showcase Your Technical Skills
Given the hands-on coding requirement, be prepared to demonstrate your proficiency in Python, C++, or R. Brush up on relevant algorithms and frameworks that are commonly used in recommender systems and LLMs.
✨Prepare for the Coding Test
The coding test is challenging and mandatory, so practice coding problems that focus on data structures, algorithms, and machine learning concepts. Use platforms like LeetCode or HackerRank to sharpen your skills.
✨Present Your Research Effectively
During the research presentation, clearly articulate your past work, focusing on its impact and relevance to real-world applications. Be ready to answer questions and defend your methodologies.
✨Demonstrate Leadership and Mentorship
Highlight your experience in mentoring junior researchers and leading projects. Discuss how you have guided research direction and collaborated with teams, as this role involves significant leadership responsibilities.
