At a Glance
- Tasks: Lead the development of scalable AI products and collaborate with cross-functional teams.
- Company: Join J.P. Morgan, a global leader in financial services, known for innovation and diversity.
- Benefits: Enjoy a diverse workplace with opportunities for growth and collaboration.
- Why this job: Be at the forefront of AI innovation, shaping the future of data analytics.
- Qualifications: PhD in a quantitative field and significant ML engineering experience required.
- Other info: We value diversity and inclusion, offering equal opportunities for all applicants.
The predicted salary is between 72000 - 108000 £ per year.
Job Description
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 Executive Director 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.
- Significant 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.
About Us
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. Visit our FAQs for more information about requesting an accommodation.
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we\’re setting our businesses, clients, customers and employees up for success.
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Generative AI - Executive Director employer: JPMorgan Chase & Co.
Contact Detail:
JPMorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Generative AI - Executive Director
✨Tip Number 1
Familiarize yourself with the latest advancements in generative AI and LLMs. Understanding the current trends and technologies will not only help you during interviews but also demonstrate your passion and commitment to the field.
✨Tip Number 2
Network with professionals in the AI and ML community. Attend conferences, webinars, or local meetups to connect with others in the industry. This can lead to valuable insights and potential referrals for the Executive Director position.
✨Tip Number 3
Showcase your leadership experience in ML engineering. Be prepared to discuss specific examples of how you've built and led teams, as well as how you've driven successful projects that align with business objectives.
✨Tip Number 4
Prepare to articulate your understanding of both technical and business aspects of AI. Being able to bridge the gap between scientific research and software engineering will be crucial in this role, so practice explaining complex concepts in simple terms.
We think you need these skills to ace Generative AI - Executive Director
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning engineering and leadership. Emphasize your PhD and any relevant projects that showcase your expertise in LLMs and AI.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data analytics. Discuss how your background aligns with the responsibilities of the Generative AI Executive Director role and how you can contribute to the company's goals.
Showcase Relevant Skills: Clearly outline your technical skills related to ML engineering, such as experience with distributed applications and frameworks like Ray or DeepSpeed. Mention your understanding of business objectives and how you can align ML solutions with them.
Highlight Collaboration Experience: Since the role involves working with cross-functional teams, provide examples of past collaborations. Describe how you have successfully worked with cloud engineering or SRE teams to deliver innovative solutions.
How to prepare for a job interview at JPMorgan Chase & Co.
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with ML engineering and the specific frameworks you've used, such as Ray or DeepSpeed. Highlight any projects where you successfully implemented scalable applications, as this will demonstrate your capability to handle the technical demands of the role.
✨Align with Business Objectives
Understand the company's goals and be ready to explain how your work in AI and ML can contribute to achieving those objectives. Discuss your experience in writing clear OKRs and how you have aligned technical projects with business needs in the past.
✨Emphasize Collaboration Skills
Since the role involves working closely with cross-functional teams, share examples of how you've successfully collaborated with cloud engineering, SRE teams, or other departments. Highlight your communication skills and ability to build trust with stakeholders at all levels.
✨Discuss Ethical AI Practices
Given the focus on responsible AI, be prepared to talk about your understanding of ethical considerations in AI development. Share any experiences you have had in ensuring that AI products are developed and deployed responsibly, and how you plan to uphold these standards in your future work.