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- Tasks: Lead AI/ML initiatives to automate complex workflows and enhance operations.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, diverse workplace, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on diversity and inclusion.
- Why this job: Shape the future of AI in finance and make a real impact.
- Qualifications: MSc/PhD in relevant fields and experience in AI application deployment.
The predicted salary is between 120000 - 150000 £ per year.
As a Director of AI/ML within the Commercial and Investment Bank, you will set the vision and lead the enterprise portfolio for agentic AI that automates and optimizes complex business workflows at scale. You will guide cross-functional teams and strategic partners to define reference architectures and delivery roadmaps for multi-agent systems—leveraging LLMs, retrieval-augmented generation, and modern agent frameworks—while instituting governance, safety, and reliability standards and tracking measurable business outcomes.
Job responsibilities
- Architect, develop, and productionize autonomous and assistive AI agents to streamline and enhance operations.
- Design multi-agent systems, including role definition, tool integration, planning, memory, and workflow orchestration using LangChain, CrewAI, AutoGen, ADK and LangGraph.
- Implement Retrieval-Augmented Generation (RAG) pipelines and semantic search using vector databases such as Pinecone and Chroma, including indexing, retrieval policies, and evaluation.
- Build and integrate agent tools (MCP) and APIs to connect agents with external services, databases, and internal systems, ensuring robust output parsing, error handling, and retries.
- Design and implement robust evaluation frameworks to systematically assess and measure the performance of AI agents across key operational metrics.
- Practice advanced prompt and context engineering (e.g., Chain-of-Thought, ReAct, function calling/tool-use prompts), implement output validation and guardrails to reduce hallucinations.
- Deploy scalable AI services to cloud infrastructure, ensuring monitoring, and observability for agent performance.
- Design microservices-based architectures and orchestrate multi-step workflows; instrument agents for tracing, metrics, and feedback loops to continuously improve reliability and utility.
- Partner with stakeholders to define requirements, design intuitive human-AI interfaces (voice, chat), and deliver measurable business impact.
- Analyze data to inform agent capabilities, optimize retrieval, and drive data-driven decision-making; and performance evaluations.
- Mentor and guide team members on agent frameworks, LLM usage, safety, and best practices.
Required qualifications
- MSc/PhD in Computer Science, Data Science, Machine Learning, or related field.
- Significant proven experience building and deploying AI applications in large scale production environments.
- Experience managing data science teams and coaching team members.
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).
- Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).
- Experience with generative models (transformers, GANs/VAEs; diffusion models a plus).
- Strong understanding of data preprocessing, feature engineering, and evaluation techniques.
- Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Strong communication skills for both technical and non-technical audiences.
Preferred qualifications
- Experience fine-tuning small language models (SLMs) with LoRA, QLoRA, DoRA; quantization and distillation a plus.
- Familiarity with prompt optimization frameworks (AutoPrompt, DSPy) and building evaluation suites.
- Experience with distributed computing, data sharding, and performance optimization.
- Hands-on with AWS AI deployment services (SageMaker, Bedrock) and workflow orchestration.
- Demonstrated experience in financial services, particularly investment banking operations.
AI/ML Director in Slough employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI/ML Director in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects. 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 practising common questions and scenarios related to AI/ML. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨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!
We think you need these skills to ace AI/ML Director in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the AI/ML Director role. Highlight your experience with agentic frameworks and any relevant projects you've led. We want to see how your skills align with our vision!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and how you can contribute to our team. Be sure to mention specific technologies and methodologies from the job description that you’re familiar with.
Showcase Your Achievements: When detailing your experience, focus on measurable outcomes. Did you improve efficiency or reduce costs in previous roles? We love numbers that tell a story about your impact!
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’s super easy!
How to prepare for a job interview at J.P. Morgan
✨Know Your AI/ML Stuff
Make sure you brush up on the latest trends and technologies in AI and ML, especially those mentioned in the job description. Be ready to discuss your experience with frameworks like LangChain and CrewAI, and how you've implemented RAG pipelines or multi-agent systems in past projects.
✨Showcase Your Leadership Skills
As a Director, you'll need to demonstrate your ability to lead cross-functional teams. Prepare examples of how you've successfully managed data science teams, mentored team members, and collaborated with stakeholders to achieve measurable business outcomes.
✨Prepare for Technical Questions
Expect deep technical questions about Python, ML frameworks, and cloud platforms. Brush up on your knowledge of containerization with Docker and Kubernetes, and be ready to explain your approach to building scalable AI services and evaluating agent performance.
✨Communicate Clearly
You’ll need to convey complex ideas to both technical and non-technical audiences. Practice explaining your past projects and technical concepts in simple terms. This will show that you can bridge the gap between tech and business, which is crucial for this role.