At a Glance
- Tasks: Lead the design and delivery of cutting-edge AI systems for financial technology.
- Company: Join J.P. Morgan, a global leader in financial services and innovation.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Why this job: Shape the future of AI in finance and make a real impact.
- Qualifications: PhD or equivalent experience in a quantitative field; extensive ML engineering background.
- Other info: Collaborative team culture focused on innovation and diversity.
The predicted salary is between 72000 - 108000 £ per year.
Step into a pivotal role at the forefront of JP Morgan’s AI transformation. As part of the Chief Analytics Office (CAO), you’ll drive innovation and shape the future of financial technology. You’ll collaborate with talented teams, architect impactful solutions, and see your work deliver measurable results across the firm. This is your opportunity to influence strategy, build production-grade systems, and unlock new possibilities for our clients and stakeholders. Join us and help define the next era of enterprise AI.
As a Generative AI Executive Director in the Chief Analytics Office, you will lead the design and delivery of production-grade LLM systems that power mission-critical products for thousands of professionals. Your technical leadership will empower teams to innovate and accelerate the adoption of AI at scale.
Job Responsibilities- You will architect scalable APIs and agentic workflows, enabling automation and efficiency across the firm.
- Architect and deliver production LLM-based systems for text, image, speech, and video applications.
- Own end-to-end delivery, performance, and continuous improvement of LLM Suite products.
- Working closely with ML Engineering, Product Management, and Cloud Engineering, you will ensure our AI solutions are reliable, secure, and built for real business impact.
- Bridge advanced AI research with robust engineering to build innovative, production-ready solutions.
- Drive results with an entrepreneurial mindset in a fast-paced, high-impact environment.
- Hold a PhD or possess equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative discipline.
- Demonstrate extensive hands-on experience in ML engineering, with a proven track record of shipping production AI systems.
- Bring deep expertise in NLP, Computer Vision, and/or Multimodal LLM algorithms, with a strong foundation in statistics, optimization, and ML theory.
- Apply practical experience implementing distributed, multi-threaded, and scalable applications using frameworks such as Ray, Horovod, or DeepSpeed.
- Communicate complex technical concepts effectively and build trust with stakeholders at all levels.
- Design and deploy production ML pipelines using DAG frameworks, including custom operator development and pipeline optimization.
- Architect and implement high-throughput, low-latency microservices with gRPC, REST, and GraphQL, including protocol buffer schema design, streaming endpoints, and load balancing.
- Apply hands-on experience with parameter-efficient fine-tuning (LoRA, QLoRA, IA3), model quantization (INT8, FP16, GPTQ), and quantization-aware training for LLMs at scale.
- Demonstrate deep knowledge of distributed training strategies, memory optimization, and inference acceleration for large-scale multimodal models.
- Orchestrate advanced agentic workflows, including multi-agent coordination, stateful task management, and integration with enterprise event-driven architectures.
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.
J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.
Generative AI Director employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Generative AI Director
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A personal connection can make all the difference when it comes to landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repository showcasing your projects and achievements. This is your chance to demonstrate your expertise in generative AI and ML engineering.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to AI and 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 noticed. Plus, you’ll find more tailored opportunities that match your skills and aspirations.
We think you need these skills to ace Generative AI Director
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Generative AI Director role. Highlight your relevant experience in ML engineering and any projects that showcase your skills in NLP and Computer Vision. We want to see how you can bring value to our team!
Showcase Your Technical Skills: Don’t hold back on detailing your technical expertise! Include specific examples of production-grade systems you've worked on, especially those involving LLMs. This is your chance to impress us with your hands-on experience and problem-solving abilities.
Communicate Clearly: When writing your application, keep it clear and concise. Use straightforward language to explain complex concepts, as this will demonstrate your ability to communicate effectively with stakeholders. Remember, clarity is key in tech roles!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our team at J.P. Morgan!
How to prepare for a job interview at hackajob
✨Know Your Stuff
Make sure you brush up on your technical knowledge, especially around ML engineering and LLM systems. Be ready to discuss your hands-on experience with NLP, Computer Vision, and any frameworks like Ray or DeepSpeed. This is your chance to showcase your expertise!
✨Showcase Your Leadership Skills
As a Generative AI Director, you'll need to demonstrate your ability to lead teams and drive innovation. Prepare examples of how you've successfully managed projects and collaborated with cross-functional teams in the past. Highlight your entrepreneurial mindset and how it has led to impactful results.
✨Communicate Clearly
You’ll be expected to explain complex technical concepts to stakeholders at all levels. Practice articulating your ideas clearly and concisely. Use relatable analogies if necessary, and ensure you can convey the business impact of your technical solutions.
✨Prepare for Scenario Questions
Expect scenario-based questions that assess your problem-solving skills and decision-making process. Think about challenges you've faced in previous roles, particularly in architecting scalable systems or optimising ML pipelines, and be ready to discuss how you overcame them.