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- Tasks: Design and deploy LLM-powered Python workflows to enhance business processes.
- Company: Global trading and investment firm with a strong focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic work environment with a commitment to ethics and integrity.
- Why this job: Join a cutting-edge team and make a real impact in AI and finance.
- Qualifications: Bachelor's degree in a technical field and experience in Python development.
The predicted salary is between 60000 - 80000 £ per year.
About Caxton Associates
Caxton Associates, founded in 1983, is a global trading and investment firm with offices in London, New York, Singapore, Monaco, Dubai and Bengaluru. Caxton Associates’ primary business is to manage client and proprietary capital through a suite of products designed to fit the specific needs of investors. Employing a multi-portfolio manager framework, Caxton excels in discretionary global macro investing, leveraging its diversified expertise across asset classes and markets.
About the role
We are seeking a Python LLM Engineer to join the Software Development team. The Software Development team is responsible for building out the next generation of highly scalable, reusable and performant distributed services and applications for Caxton users.
- Design and deploy LLM-powered Python workflows that integrate into existing business processes.
- Implement retrieval-augmented generation (RAG) and related architectures to ground LLM outputs in Caxton’s proprietary data.
- Architect secure data integrations, linking models to internal knowledge bases, APIs, and document repositories.
- Automate manual research and operational workflows, delivering measurable efficiency and quality improvements.
- Build and maintain robust data pipelines for document parsing, enrichment, and structured data extraction.
- Develop maintainable, testable Python code to support scalable AI services in production.
- Run pilots and proofs of concept, demonstrating value and best practices for AI adoption across the organization.
- Troubleshoot and optimize model performance, retrieval accuracy, and infrastructure reliability.
- Stay current on advances in LLMs, prompt engineering, and applied machine learning; evaluate and prototype emerging methods.
Experience
- Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related technical field.
- Experience in Python development.
- Experience deploying and supporting Python applications and workflows.
- Familiarity with multi-modal data integration and distributed inference architectures.
- Strong problem-solving and communication skills.
- Some knowledge of cloud services – e.g. AWS/Azure would be beneficial.
- Displays and operates at the highest degree of ethics and integrity.
Python LLM Engineer in London employer: Caxton Associates
Contact Detail:
Caxton Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python LLM Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Caxton Associates. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially any LLM-related work. This gives us a tangible way to see what you can do.
✨Tip Number 3
Prepare for the interview by brushing up on your problem-solving skills. Expect technical questions that test your knowledge of Python and LLMs. Practice makes perfect!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly.
We think you need these skills to ace Python LLM Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Python LLM Engineer role. Highlight your experience with Python development and any relevant projects that showcase your skills in building scalable applications. We want to see how you can fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with our needs at Caxton Associates. Be genuine and let your personality come through – we love that!
Showcase Your Projects: If you've worked on any cool projects related to LLMs or Python workflows, make sure to mention them! We’re interested in seeing real examples of your work, so don’t hold back on sharing your achievements and what you learned from them.
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 us you’re keen on joining our team at Caxton Associates!
How to prepare for a job interview at Caxton Associates
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python development, especially in relation to building scalable applications and workflows. Practise coding challenges that focus on data manipulation and automation, as these are likely to come up.
✨Understand LLMs and RAG
Familiarise yourself with the concepts of large language models (LLMs) and retrieval-augmented generation (RAG). Be prepared to explain how you would implement these technologies in a practical setting, particularly in relation to integrating them into existing business processes at Caxton Associates.
✨Showcase Your Problem-Solving Skills
During the interview, be ready to tackle hypothetical scenarios or case studies that test your problem-solving abilities. Think about how you would troubleshoot model performance or optimise infrastructure reliability, and articulate your thought process clearly.
✨Stay Current and Be Curious
Demonstrate your passion for the field by discussing recent advancements in LLMs and applied machine learning. Show that you’re proactive about learning and adapting to new technologies, which is crucial for a role that involves evaluating and prototyping emerging methods.