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For Companies At a Glance
- Tasks: Lead the development of innovative AI products and collaborate with cross-functional teams.
- Company: Join a forward-thinking organisation at the forefront of AI and data analytics.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Be a key player in revolutionising AI technology and making a real impact.
- Qualifications: PhD in a quantitative field and experience in ML engineering required.
- Other info: Dynamic environment with a focus on ethical AI practices and collaboration.
The predicted salary is between 72000 - 108000 £ per year.
We are thrilled to introduce you to our team at the Chief Data and Analytics Office (CDAO) organization. As the driving force behind the firmwide adoption of artificial intelligence (AI) across our company, our dedicated team is responsible for overseeing data use, governance, and controls around the build, adoption and maintenance of cloud infrastructure, data and AI/ML products. With a focus on both effectiveness and responsibility, we strive to push the boundaries of innovation while ensuring ethical and sustainable practices. Join us on this exciting journey as we revolutionize the way we leverage data and analytics to shape the future of our organization.
As a Generative AI Vice President within our CDAO organization, you will play a crucial role in ensuring the smooth operation and optimization of our LLM aided AI products. Our firm-wide team focuses on developing scalable LLM-based products and reusable back-end APIs. You will engage in close collaboration with cross-functional teams, including the ML Centre of Excellence, AI Research, Cloud Engineering, and others, to foster innovation and deliver solutions that yield a high Return-on-Investment (RoI). You will ensure that our APIs are built with scalability in mind, allowing them to efficiently handle a large number of requests without compromising performance. By designing APIs with a clear separation of concerns and well-defined interfaces, we enable other teams and developers to leverage our APIs to build their own ML products and solutions, fostering a culture of collaboration and efficiency.
Job Responsibilities
- Combine vast data assets with cutting-edge AI, including LLMs and Multimodal LLMs.
- Bridge scientific research and software engineering, requiring expertise in both domains.
- Collaborate closely with cloud and SRE teams while leading the design and delivery of production architectures.
Required qualifications, capabilities, and skills
- PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics.
- Experience in an individual contributor role in ML engineering.
- Proven track record in building and leading teams of experienced ML engineers/scientists.
- Solid understanding of the fundamentals of statistics, optimization, and ML theory, focusing on NLP and/or Computer Vision algorithms.
- Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.).
- Ability to understand and align with business expectations, and write clear and concise OKRs (Objectives and Key Results).
- Experience as a "Responsible Owner" for ML services in enterprise environments.
- Excellent grasp of computer science fundamentals and SDLC best practices.
- Ability to understand business objectives and align ML problem definition.
- Strong communication skills to effectively convey technical information and ideas at all levels, building trust with stakeholders.
Preferred qualifications, capabilities, and skills
- Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray).
- Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints.
- Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models.
- Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.
Generative AI - Vice President in City of London employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Generative AI - Vice President in City of London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or conferences related to AI and data analytics. We can’t stress enough how important it is to build relationships; you never know who might have the inside scoop on job openings.
✨Show Off Your Skills
Don’t just talk about your experience—show it! Create a portfolio showcasing your projects, especially those involving LLMs or AI products. We love seeing practical examples of your work, so make sure to highlight your achievements and the impact they had.
✨Ace the Interview
Prepare for interviews by brushing up on both technical and soft skills. We recommend practising common interview questions and scenarios specific to ML engineering. Remember, it’s not just about what you know, but how you communicate your ideas and collaborate with others.
✨Apply Through Our Website
When you find a role that excites you, apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals ready to join us in revolutionising the world of data and analytics.
We think you need these skills to ace Generative AI - Vice President in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Generative AI Vice President role. Highlight your expertise in ML engineering, cloud infrastructure, and any relevant projects that showcase your ability to lead teams and innovate.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you're passionate about AI and how your background makes you the perfect fit for our CDAO team. Be sure to mention specific experiences that demonstrate your understanding of both technical and business aspects.
Showcase Your Technical Skills: In your application, don’t shy away from detailing your technical prowess. Mention any hands-on experience with LLMs, distributed applications, or frameworks like Ray and DeepSpeed. We want to see how you can contribute to our innovative projects!
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 gives you a chance to explore more about our team and culture!
How to prepare for a job interview at J.P. Morgan
✨Know Your Stuff
Make sure you brush up on the latest trends in generative AI, especially around LLMs and multimodal models. Be ready to discuss your hands-on experience with frameworks like Ray or DeepSpeed, as well as your understanding of NLP and computer vision algorithms.
✨Showcase Collaboration Skills
Since this role involves working closely with cross-functional teams, prepare examples that highlight your collaborative efforts. Think about times when you successfully bridged gaps between data science and software engineering, and how you fostered innovation in those situations.
✨Align with Business Goals
Be prepared to discuss how your technical expertise aligns with business objectives. Practice articulating how you've defined OKRs in previous roles and how you can ensure that ML solutions deliver a high Return-on-Investment for the company.
✨Communicate Clearly
Strong communication is key, so practice explaining complex technical concepts in simple terms. Think about how you can build trust with stakeholders by conveying your ideas clearly and concisely, ensuring everyone is on the same page.
