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- Tasks: Train and fine-tune large language models for real enterprise applications.
- Company: Innovative AI company in Manchester with a hybrid work culture.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Join a cutting-edge team shaping the future of AI communication tools.
- Qualifications: MSc or PhD in relevant fields and strong Python skills required.
- Other info: Dynamic environment with a focus on research and collaboration.
The predicted salary is between 36000 - 60000 £ per year.
Location: Manchester, UK (Hybrid – 3 days in the office)
Build the Future of AI-Powered Communication
We’re looking for a Data Scientist to join our growing LLM team, building production-ready large language models that power real enterprise applications. You’ll help train models, create datasets, and push performance boundaries in a fast-moving, research-driven environment.
What You’ll Do
- Train and fine-tune LLMs and ML models using standardised experiments and high-quality data.
- Build and improve LLM-based systems for low-latency RAG systems, intent detection, call scoring, and email classification.
- Support real-time inference infrastructure with ultra-low latency and detailed monitoring.
- Create and maintain evaluation datasets to test safety, prompt following, and conversational quality.
- Collaborate with engineers and researchers to apply new ideas from the latest LLM and ML research.
What We’re Looking For
- MSc or PhD in Computer Science, Data Science, Mathematics, Physics, or a related field.
- Strong Python skills (pandas, NumPy, scikit-learn, PyTorch).
- Curiosity, rigour, and drive to improve model performance.
Why Join Us
- Work on real applied LLMs from training to deployment.
- Collaborate with an ambitious, research-informed team.
- Shape the next generation of AI-driven communication tools.
Data Scientist (LLMs) employer: ConnexAI
Contact Detail:
ConnexAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (LLMs)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLMs and ML models. It’s a great way to demonstrate your expertise beyond the application.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and practical coding challenges. We recommend practicing with real-world problems to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining us.
We think you need these skills to ace Data Scientist (LLMs)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience and skills, especially in Python and data science. We want to see how your background aligns with the role of a Data Scientist in LLMs, so don’t hold back on showcasing your projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and LLMs, and how your curiosity and drive can contribute to our team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any relevant projects, whether academic or personal, make sure to mention them. We’re interested in seeing how you’ve applied your skills in real-world scenarios, especially in training and fine-tuning models.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen to join our team at StudySmarter!
How to prepare for a job interview at ConnexAI
✨Know Your Models
Make sure you brush up on the latest advancements in large language models. Be ready to discuss your experience with training and fine-tuning models, as well as any specific projects you've worked on that relate to LLMs.
✨Showcase Your Python Skills
Since strong Python skills are a must, prepare to demonstrate your proficiency with libraries like pandas, NumPy, and PyTorch. Consider bringing along a portfolio of code snippets or projects that highlight your abilities.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of machine learning concepts and algorithms. Brush up on topics like intent detection and low-latency systems, and be ready to explain how you would approach building and improving these systems.
✨Emphasise Collaboration
This role involves working closely with engineers and researchers, so be prepared to discuss your teamwork experiences. Share examples of how you've collaborated on projects and applied new ideas from research to real-world applications.