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- Tasks: Design and build cutting-edge NLP systems for finance.
- Company: Join a dynamic Series A startup revolutionising financial infrastructure.
- Benefits: Enjoy a collaborative culture with opportunities for growth and innovation.
- Why this job: Be part of a forward-thinking team using AI to reshape finance.
- Qualifications: Strong Python skills and experience with LLMs and full-stack development required.
- Other info: Work with modern tools like Langchain, FastAPI, and Docker.
The predicted salary is between 36000 - 60000 £ per year.
We are searching for a Machine Learning Researcher / Data Scientist to join a Series A startup on a mission to modernise outdated financial infrastructure! They are using cutting-edge tech to build smarter, faster systems that rethink how finance works from the ground up. This collaborative, forward-thinking team is building powerful, AI-driven solutions using open-source LLMs, replacing outdated systems with sleek, scalable tech within Asset Management.
They are now hiring a Machine Learning Engineer with a strong Python background and hands-on experience with LLMs, Langchain, and full-stack product development.
You’ll be:
- Designing & building production-grade NLP systems
- Integrating in-house and open-source models
- Collaborating with a cross-functional team of top engineers and product minds
- Working with tools e.g. Langchain, FastAPI, Docker, cloud platforms
Interested? Apply now!
Contact Detail:
Understanding Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Researcher
✨Tip Number 1
Familiarise yourself with the latest advancements in NLP and LLMs. Being able to discuss recent trends or breakthroughs during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Showcase your hands-on experience with Python and relevant frameworks like Langchain and FastAPI. Prepare to discuss specific projects where you've implemented these technologies, as practical examples can set you apart.
✨Tip Number 3
Highlight your collaborative skills by preparing examples of how you've worked effectively in cross-functional teams. This role values teamwork, so demonstrating your ability to communicate and collaborate will be key.
✨Tip Number 4
Research the company’s mission and values thoroughly. Understanding their approach to modernising financial infrastructure will allow you to align your answers with their goals during the interview.
We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, LLMs, and any relevant projects. Use specific examples that demonstrate your skills in designing and building NLP systems.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's mission to modernise financial infrastructure. Mention how your background aligns with their needs and your passion for AI-driven solutions.
Showcase Relevant Projects: If you have worked on projects involving Langchain, FastAPI, or Docker, be sure to include these in your application. Describe your role and the impact of these projects to illustrate your hands-on experience.
Highlight Collaboration Skills: Since the role involves working with a cross-functional team, emphasise your ability to collaborate effectively. Provide examples of past teamwork experiences that showcase your communication and problem-solving skills.
How to prepare for a job interview at Understanding Recruitment
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, LLMs, and Langchain in detail. Bring examples of projects you've worked on that demonstrate your ability to design and build production-grade NLP systems.
✨Understand the Company’s Mission
Research the startup's mission to modernise financial infrastructure. Be ready to explain how your skills and experiences align with their goals and how you can contribute to their innovative approach in the FinTech space.
✨Prepare for Collaborative Scenarios
Since the role involves working with a cross-functional team, think of examples where you've successfully collaborated with others. Highlight your communication skills and how you handle feedback and differing opinions.
✨Familiarise Yourself with Relevant Tools
Brush up on tools like FastAPI, Docker, and cloud platforms that are mentioned in the job description. Being able to discuss your familiarity with these technologies will show your readiness to hit the ground running.
