At a Glance
- Tasks: Join us to research and develop cutting-edge speech-to-speech capabilities in multimodal LLMs.
- Company: ConnexAI is an innovative tech company focused on enhancing language models with advanced speech technologies.
- Benefits: Enjoy a collaborative work environment, opportunities for growth, and the chance to shape groundbreaking technology.
- Other info: Ideal for those passionate about research and eager to learn in a dynamic team setting.
- Why this job: Be part of a greenfield project that merges speech and language, making a real impact in AI.
- Qualifications: PhD or MSc in machine learning/data science, with experience in LLMs and strong Python skills required.
The predicted salary is between 36000 - 60000 € per year.
Data Scientist (LLMs & Conversational AI)
About the role
We are building production conversational AI systems powered by large language models, speech AI, and real-time AI workflows.
We’re hiring two Data Scientists to join our LLM team, helping design, improve, and evaluate the systems that power our Conversational AI products in production. The focus is on defining, interrogating and solving complex modelling and evaluation problems, and building the data and experimentation foundations that will generate systematic advances in conversational AI.
You’ll work closely with researchers, engineers, and evaluation teams across areas such as LLM behaviour and reasoning, prompt optimisation, conversational quality, and model evaluation.
We’re particularly interested in people from strong quantitative backgrounds including Mathematics, Physics, Statistics, Computer Science, or related fields, who enjoy piecing together difficult problems, thinking rigorously, and working in environments driven by research and experimentation.
What you’ll do
- Design and use datasets, experiments and evaluation methods to gain detailed and intimate knowledge of our conversational AI solutions.
- Identify opportunities to improve quality, reliability, and performance through research and experimentation
- Statistically investigate how changes to prompts, pipelines, models, or system logic impact real-world outcomes
- Think creatively about edge cases that might expose flaws in a system, and devise and test different ideas about how to handle those cases without harming global performance
- Develop tests and metrics that capture the many nuances of user requirements, rather than uncritically relying on industry-standard proxies that might obscure underlying issues
- Advance the building blocks behind LLM-powered systems, including classification, ranking, retrieval, scoring, and conversational workflows
- Collaborate with engineering and evaluation teams to turn product problems into measurable AI problems
- Stay up to date with the latest research and critically apply new ideas to production AI systems, separating out strong, flexible approaches from fragile hype
What we’re looking for
- Degree, MSc, or PhD in Mathematics, Physics, Statistics, Computer Science, or a similarly quantitative field
- Strong Python skills with experience using tools such as pandas, NumPy, and scikit-learn
- Experience working with data science, experimentation, statistical analysis, or machine learning systems
- Curiosity around the finer details of LLMs, NLP, or conversational AI
- Ability to think critically about model behaviour and system performance rather than simply training models
- Sceptical mindset: you are uncomfortable with taking any assumption as given, and you examine new ideas with an open but critical mind
- Comfortable working in fast-moving, collaborative environments with ambiguous problems
- Work on real-world conversational AI systems used in production
- Solve difficult applied AI problems in a highly collaborative environment
- Join a research-driven team working across LLMs, speech AI, and evaluation
- Influence how AI systems are measured, improved, and deployed at scale
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in Manchester
✨Tip Number 1
Familiarise yourself with the latest research in multimodal LLMs and speech technologies. Being able to discuss recent academic papers during interviews will demonstrate your commitment to staying updated in this rapidly evolving field.
✨Tip Number 2
Showcase any hands-on projects or contributions you've made in machine learning, particularly those involving speech-to-text or text-to-speech systems. Real-world examples can significantly strengthen your case as a candidate.
✨Tip Number 3
Network with professionals in the field of data science and machine learning, especially those focused on speech technologies. Engaging in relevant online communities or attending industry events can help you make valuable connections.
✨Tip Number 4
Prepare to discuss how you would approach integrating audio data into multimodal systems. Having a clear strategy or ideas ready can set you apart from other candidates and show your problem-solving skills.
We think you need these skills to ace Data Scientist in Manchester
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in machine learning, data science, and any specific projects related to speech technologies or multimodal systems. Use keywords from the job description to align your skills with what ConnexAI is looking for.
Craft a Compelling Cover Letter:In your cover letter, express your passion for the intersection of speech and language technologies. Discuss specific projects or research that demonstrate your expertise in LLMs and how you can contribute to ConnexAI's ambitious goals.
Showcase Your Research Experience:If you have published papers or conducted significant research, summarise these experiences in your application. Highlight any work related to audio data integration or model training that aligns with the role's requirements.
Prepare for Technical Questions:Anticipate technical questions related to machine learning, programming in Python, and using frameworks like PyTorch. Be ready to discuss your approach to implementing techniques from academic papers into practical solutions during potential interviews.
How to prepare for a job interview at ConnexAI
✨Showcase Your Research Background
Make sure to highlight your research experience in machine learning, especially if it relates to speech or multimodal systems. Be prepared to discuss specific projects or papers you've worked on and how they relate to the role.
✨Demonstrate Technical Proficiency
Since strong programming skills in Python and experience with PyTorch are essential, be ready to discuss your coding experience. You might even want to prepare for a technical assessment or coding challenge during the interview.
✨Prepare for Collaborative Scenarios
Given the collaborative nature of the role, think of examples where you've successfully worked in interdisciplinary teams. Be ready to discuss how you communicate complex ideas to non-technical team members.
✨Stay Curious and Open to Learning
Express your curiosity and willingness to learn new techniques and technologies. This role involves adapting recent academic findings into practical solutions, so showing enthusiasm for continuous learning will set you apart.
