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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer Analyst - **Company:** Cerberus Capital Management - **Location:** London, UK - **Experience:** Starter - **Contract:** Internship / Graduate position - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Computer Programming, Information Engineering, Database Queries, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Simple Data Format, Software Deployment, Software Engineering, Data Processing, Model-Driven Development, Large Language Models, Machine Learning Operations, Tools for Reporting, Data Pipelines, GXP - **Published:** May 14, 2026 - **Apply:** https://www.gradsouthwest.com/jobs/ai-engineer-analyst-london/2770439349-2/ ## About the Role + PhD graduates in a STEM field with applied ML, optimization, or computational experience; or + Bachelor's/Master's graduates with 1-2 years of industry experience or relevant internships in machine learning, data engineering, or software engineering. You'll contribute to designing, implementing, and deploying production-grade ML systems-ranging from NLP pipelines to model driven workflow automation. You'll 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 ## Description Work with senior engineers to design, train, and deploy machine learning models and data-driven tools that support investment and operational decision-making. Contribute to real production deployments Help integrate ML models into business workflows, build data pipelines, and support the rollout of AI applications across teams. Experiment and iterate Prototype ideas, test assumptions, and rapidly evolve solutions based on real user feedback and real-world constraints. Learn modern tooling and practices Gain hands-on experience with ML frameworks, cloud infrastructure, MLOps tools, and best practices for building scalable AI systems. Communicate clearly Translate technical findings into clear, structured insights for collaborators across technical and business teams. Grow as an AI engineer Develop skills across the full ML lifecycle-data processing, modelling, evaluation, deployment, and ongoing improvement. Sample Projects You Might Work On GenAI for due diligence Support the configuration, extension, and rollout of our in-house GenAI platform across investment teams. Work with senior engineers to customise workflows, analyse model outputs, and drive adoption. Automated Deal Sourcing Tools Help build prototypes that extract signals from datasets and integrate with APIs to enrich leads. Support the creation of modular ML-driven components that can be used across investment strategies. (Both examples are reframed so junior team members contribute meaningfully but are not expected to independently lead full workstreams.) ## Related Videos - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? 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