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- Tasks: Design and optimise AI systems for cutting-edge portfolio management solutions.
- Company: Join a leading tech firm at the forefront of AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Be a key player in shaping the future of AI applications in finance.
- Qualifications: PhD or Master's in a technical field with strong Python and AI experience.
- Other info: Dynamic team environment with a focus on collaboration and impact.
The predicted salary is between 36000 - 60000 £ per year.
We are building the next generation of Large Language Model applications driven by Portfolio Manager requirements that deliver immediate value and scale as a core product. We are looking for an AI Engineer to lead this work within the Equities Technology AI group. This role will be responsible for designing, expanding, and optimizing the architecture of a strategic, evolving AI platform. The ideal candidate is an experienced engineer who enjoys building and owning high-performance, production-grade AI systems from the ground up.
Responsibilities:
- Understand and translate Portfolio Manager and business problems into robust, production-ready AI solutions.
- Design, build, test, deploy, and own LLM-based products that solve specific Portfolio Manager workflows and generalize into reusable AI capabilities.
- Design and implement agentic AI systems that perform multi-step reasoning, planning, and tool execution.
- Own the end-to-end LLM architecture and lifecycle, including prompt design, model selection, evaluation, deployment, and iteration.
- Identify, design, and implement internal process and infrastructure improvements with a focus on scalability, reliability, and performance.
- Work closely with stakeholders across business and technology organizations to optimize product design and adoption in production environments.
Qualifications:
- PhD in a technical field with 5+ years of industry experience, or Master’s degree with equivalent industry experience.
- Strong Python engineering experience, including object-oriented design, microservices, and REST API development.
- Hands-on experience building and operating production-grade LLM applications.
- Experience with agentic and LLM frameworks.
- Strong understanding of agentic patterns including tool use, planning, memory, and reflection.
- Experience with retrieval-augmented generation, vector databases, and semantic search systems.
- Experience fine-tuning or adapting models using techniques such as LoRA or PEFT.
- Experience developing end-to-end asynchronous applications and distributed systems.
- Experience deploying AI systems in cloud environments such as AWS or GCP.
- Strong interpersonal and communication skills with the ability to operate independently and collaboratively in a fast-paced environment.
AI Engineer - Equities Technology. in London employer: Millennium Management
Contact Detail:
Millennium Management Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer - Equities Technology. in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to LLM applications. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail, especially how they relate to the role of an AI Engineer.
✨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 proactive about their job search!
We think you need these skills to ace AI Engineer - Equities Technology. in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of AI Engineer in Equities Technology. Highlight your experience with LLM applications and Python engineering, and don’t forget to mention any relevant projects that showcase your skills!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how your background aligns with our mission at StudySmarter. Be specific about how you can contribute to building high-performance AI systems.
Showcase Your Projects: If you've worked on any production-grade AI systems or have experience with agentic frameworks, make sure to include those in your application. We love seeing real-world examples of your work that demonstrate your problem-solving skills!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Millennium Management
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI systems, especially Large Language Models. Be ready to discuss your hands-on experience with production-grade applications and how you've tackled real-world problems using AI.
✨Showcase Your Python Skills
Since strong Python engineering experience is key, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice object-oriented design and REST API development beforehand.
✨Understand the Business Context
Familiarise yourself with the role of Portfolio Managers and their workflows. Be prepared to explain how your AI solutions can directly address their needs and improve their processes. This shows you can translate technical skills into business value.
✨Communicate Effectively
Strong interpersonal skills are crucial, so practice articulating your thoughts clearly. Be ready to discuss your past experiences in collaborative environments and how you’ve worked with stakeholders to optimise product design and adoption.
