At a Glance
- Tasks: Design and deploy machine learning models to support investment decisions and operational efficiency.
- Company: Join a dynamic team transforming data use in a global investment firm.
- Benefits: Competitive salary, hands-on experience, and rapid career growth opportunities.
- Other info: Work alongside AI specialists and gain exposure across various investment strategies.
- Why this job: Make a real impact with AI while collaborating in a fast-paced, innovative environment.
- Qualifications: PhD or 1-2 years of experience in ML, software, or data engineering.
The predicted salary is between 40000 - 50000 £ per year.
Responsibilities
- Design, train, and deploy machine learning models and data-driven tools to support investment and operational decision-making.
- Contribute to real production deployments of AI systems.
- Integrate ML models into business workflows, build data pipelines, and support rollout of AI applications across teams.
- Prototype ideas, test assumptions, and rapidly evolve solutions based on real user feedback and real-world constraints.
- Translate technical findings into clear, structured insights for collaborators across technical and business teams.
- Develop skills across the full ML lifecycle including data processing, modelling, evaluation, deployment, and ongoing improvement.
- Learn modern tooling and practices such as ML frameworks, cloud infrastructure, and MLOps tools for scalable AI systems.
Sample Projects You Might Work On
- GenAI for due diligence - support configuration, extension, and rollout of an in-house GenAI platform across investment teams; customise workflows, analyse model outputs, and drive adoption.
- Automated Deal Sourcing Tools - build prototypes that extract signals from datasets and integrate with APIs to enrich leads; support creation of modular ML-driven components usable across investment strategies.
Qualifications
- PhD graduates in a STEM field with applied ML, optimisation, or computational experience.
- Bachelor's/Master's graduates with 1-2 years of industry experience or relevant internships in machine learning, data engineering, or software engineering.
You will contribute to designing, implementing, and deploying production-grade ML systems ranging from NLP pipelines to model-driven workflow automation. You will learn quickly, gain real ownership, and see your work make tangible business impact. We don't expect candidates to have experience across all areas - what matters most is strong technical fundamentals, curiosity, and a willingness to learn quickly.
Foundational Skills
- Degree in a STEM field.
- PhD candidates: applied research involving ML, optimisation, simulation, statistics, numerical methods, NLP, or related areas.
- Bachelor's/Master's: 1-2 years of industry experience or relevant internships in ML, software engineering, or data engineering.
Programming Experience (especially Python)
- Experience writing clean, maintainable Python code.
- Applied AI experience such as exposure to LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.) and experience with small personal or internship projects building agents or AI-driven workflows.
- Agentic frameworks in Python is a plus but not required.
Data and Analytical Skills
- Comfortable working with data, performing analysis, and writing SQL queries.
- Experience building simple data pipelines or transformation workflows is a plus.
Exposure to ML Ops or Production Systems (Nice to Have)
- Familiarity with tools like MLflow, Weights & Biases, or cloud platforms (Azure, AWS, or GCP).
- Experience deploying models via APIs or lightweight services is a bonus, not a requirement.
Software Engineering Basics
- Understanding of Git/GitHub/Azure DevOps, testing basics, and general good engineering practices.
Mindset
- Strong problem-solving skills.
- Curiosity and eagerness to learn.
- Pragmatic, impact-driven approach.
- Ability to work collaboratively in a fast-paced environment.
About the Team
We are a growing team of AI specialists - data scientists, ML engineers, software engineers, and technology strategists - working to transform how a global investment firm with 65B+ in assets uses data and AI. We operate like a startup within the firm: fast, collaborative, and focused on delivering real value. Our work spans investment desks, portfolio companies, and core operations, giving early-career engineers wide exposure and the opportunity to grow rapidly.
AI Engineer Analyst in City of Westminster employer: Cerberus Capital Management
As an AI Engineer Analyst at our innovative global investment firm, you will thrive in a dynamic and collaborative environment that values your contributions and fosters rapid professional growth. With access to cutting-edge technology and the opportunity to work on impactful projects, you'll be part of a team that operates like a startup, driving real change across investment strategies while developing your skills in machine learning and data engineering. Our commitment to employee development and a culture of curiosity ensures that you will not only see the tangible results of your work but also continuously evolve in your career.
Contact Details:
Cerberus Capital Management Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer Analyst in City of Westminster
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow AI enthusiasts. 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 projects, especially those involving machine learning and data pipelines. This gives potential employers a taste of what you can do and sets 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. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining our team. Plus, it shows you're proactive and genuinely interested in the role.
We think you need these skills to ace AI Engineer Analyst in City of Westminster
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the AI Engineer Analyst role. Highlight any relevant projects or internships, especially those involving machine learning or data engineering.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're excited about this position and how your background makes you a great fit. Be sure to mention specific projects or experiences that relate to the responsibilities outlined in the job description.
Showcase Your Technical Skills:Don’t shy away from detailing your programming experience, especially with Python. If you've worked with ML frameworks or cloud platforms, make sure to include that info as it’s super relevant for us!
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!
How to prepare for a job interview at Cerberus Capital Management
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals before the interview. Be ready to discuss concepts like model training, evaluation, and deployment. This will show that you have a solid foundation and are eager to apply your knowledge in real-world scenarios.
✨Showcase Your Projects
Prepare to talk about any relevant projects you've worked on, especially those involving Python and machine learning. Highlight your role, the challenges you faced, and how you overcame them. This gives interviewers insight into your practical experience and problem-solving skills.
✨Understand the Business Impact
Familiarise yourself with how AI can drive business decisions, particularly in investment contexts. Be ready to discuss how your technical skills can translate into actionable insights for teams. This shows that you’re not just a techie but also understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about the team’s projects and the company’s approach to AI. This demonstrates your curiosity and eagerness to learn. It also helps you gauge if the company culture aligns with your values and career goals.
