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For Companies At a Glance
- Tasks: Dive into data, develop cutting-edge models, and solve unique challenges in NLP and LLMs.
- Company: Join a leading conversational AI company focused on delivering real-world value through innovative solutions.
- Benefits: Enjoy a hybrid work model, collaborative environment, and opportunities for continuous learning and growth.
- Why this job: Be part of a dynamic team that values creativity, innovation, and excellence in data science.
- Qualifications: 1+ years in Data Science, proficiency in Python, and a passion for pushing model performance.
- Other info: Curiosity and a willingness to learn are key—NLP experience is a plus but not required.
The predicted salary is between 28800 - 48000 £ per year.
Role: Data Scientist – Multimodal LLMs (Speech Focus)
About the Role?
ConnexAI is developing an ambitious new product to enhance our large language models with speech-to-speech capabilities. This greenfield project offers a unique opportunity to help define its research direction and build the machine learning systems that will power it.
We’re seeking a data scientist with a strong research background in machine learning and a focus on speech or multimodal systems. In this role, you’ll work at the intersection of speech and language technologies, exploring how to integrate these modalities into deployable models. You’ll collaborate closely with engineers, researchers, and product leaders to design, prototype, and deploy state-of-the-art models.
What You\’ll Be Doing?
- Researching the state-of-the-art approaches for incorporating audio data into multimodal LLMs for speech-to-text, text-to-speech, and speech-to-speech tasks
- Implementing and adapting techniques from recent academic papers into practical, production-ready solutions
- Training and fine-tuning models, and iterating on architectures to improve performance and scalability
- Sourcing, curating, and preparing datasets for model training and evaluation
- Defining evaluation metrics and testing frameworks for multimodal systems
- Collaborating with product and engineering teams to translate research concepts into deployable features
- Contributing to improving the team’s workflows to help foster a healthy, productive, and innovation-focused environment
What We\’re Looking For?
- Background in machine learning or data science, ideally with a research focus (PhD or MSc with equivalent industry experience)
- Experience working with LLMs, speech technologies (ASR, TTS), or multimodal systems
- Strong programming skills in Python, with experience in using PyTorch
- Hands-on experience with training and fine-tuning ML models, including setting up experiments and evaluating results
- Ability to read, interpret, and implement techniques from recent academic papers into practical, working solutions
- Strong communicator, comfortable working across interdisciplinary teams
- A collaborative mindset and interest in helping improve team workflows
- Curiosity and a willingness to learn
Data Scientist employer: ConnexAI
Contact Detail:
ConnexAI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarize yourself with the latest advancements in NLP and LLMs. Engage with recent research papers and online courses to deepen your understanding, as this will not only enhance your knowledge but also demonstrate your commitment to staying current in the field.
✨Tip Number 2
Showcase your problem-solving skills by discussing specific projects where you've tackled unique challenges. Be prepared to explain your thought process and the innovative tools you used, as this will highlight your ability to think critically and creatively.
✨Tip Number 3
Network with professionals in the data science community, especially those focused on NLP and LLMs. Attend meetups, webinars, or conferences to connect with like-minded individuals and gain insights that could be beneficial during your application process.
✨Tip Number 4
Prepare to discuss how you ensure data integrity and quality in your work. Being able to articulate your approach to maintaining high standards in datasets will resonate well with our focus on delivering impactful results.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Data Science, especially any work related to NLP and LLMs. Use specific examples that demonstrate your skills and achievements in these areas.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your curiosity-driven approach. Mention any specific projects or experiences that relate to the job description, particularly those involving model performance and data integrity.
Showcase Your Technical Skills: In your application, emphasize your proficiency in Python and relevant libraries like pandas, NumPy, scikit-learn, and PyTorch. If you have experience with NLP concepts or transformer models, be sure to include that as well.
Express Your Willingness to Learn: Highlight your eagerness to stay current with research and your commitment to continuous improvement. Mention any recent papers you've read or techniques you've learned that are relevant to the role.
How to prepare for a job interview at ConnexAI
✨Show Your Passion for Data Science
Make sure to express your enthusiasm for data science and your curiosity-driven approach. Share specific examples of how you've tackled challenges in the past, especially those related to model performance and data integrity.
✨Highlight Relevant Experience
Discuss your experience with machine learning techniques and any projects you've worked on that involved NLP or LLMs. Even if your background isn't strictly in these areas, emphasize your willingness to learn and adapt.
✨Demonstrate Technical Proficiency
Be prepared to talk about your proficiency in Python and the libraries mentioned in the job description, such as pandas, NumPy, scikit-learn, and PyTorch. Consider discussing a project where you utilized these tools effectively.
✨Stay Current with Research
Show that you are engaged with the latest developments in data science by mentioning any recent papers you've read or research you've followed. This demonstrates your commitment to continuous learning and staying ahead in the field.
