Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead AI projects to revolutionise business decisions and automate processes in finance.
- Company: Join JPMorgan's innovative Commercial & Investment Bank team.
- Benefits: Competitive salary, career growth, and the chance to work with cutting-edge technology.
- Why this job: Make a real impact by advancing AI in financial services.
- Qualifications: PhD in a quantitative field and hands-on ML engineering experience required.
- Other info: Dynamic role with opportunities for management and collaboration across teams.
The predicted salary is between 36000 - 60000 £ per year.
Take a technical leadership position within JPMorgan's Commercial & Investment Bank, where you'll harness cutting-edge AI techniques to revolutionize business decisions and automate processes. As an Applied AI / ML Lead – Vice President - Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining cutting‑edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state‑of‑the‑art in AI as applied to financial services, leveraging the latest research from fields of Natural Language Processing, Computer Vision, and statistical machine learning. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI‑powered products and services and increasing opportunity for re-use of foundational components through careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets. The role is initially that of an individual contributor, though there will be optional opportunity for management responsibility dependent on the candidate’s experience.
Job responsibilities
- Build robust Data Science capabilities which can be scaled across multiple business use cases
- Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems
- Research and analyse data sets using a variety of statistical and machine learning techniques
- Communicate AI capabilities and results to both technical and non-technical audiences
- Document approaches taken, techniques used and processes followed to comply with industry regulation
- Collaborate closely with cloud and SRE teams while taking a leading role in the design and delivery of the production architectures for our solutions
Required qualifications, capabilities, and skills
- Hands on experience in an ML engineering role
- PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics
- Track record of developing, deploying business critical machine learning models
- Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc
- Experience monitoring, maintaining, enhancing existing models over an extended time period
- Specialism in NLP or Computer Vision
- Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.)
- Extensive experience with pytorch, numpy, pandas
- Knowledge of open source datasets and benchmarks in NLP / Computer Vision
- Hands‑on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.)
- Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.
Preferred qualifications, capabilities, and skills
- Experience designing/implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray)
- Experience of big data technologies (e.g. Spark, Hadoop)
- Have constructed batch and streaming microservices exposed as REST/gRPC endpoints
- Familiarity with GraphQL
Applied AI ML Lead - Senior Machine Learning Engineer employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AI ML Lead - Senior Machine Learning Engineer
✨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 a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AI and ML. This is your chance to shine and demonstrate what you can bring to the table.
✨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 get comfortable.
✨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 Applied AI ML Lead - Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Applied AI ML Lead. Highlight your hands-on experience in ML engineering and any relevant projects that showcase your skills in NLP or Computer Vision. We want to see how your background aligns with what we're looking for!
Showcase Your Projects: Include specific examples of machine learning models you've developed and deployed. If you've worked on business-critical projects, let us know! This will help us understand your practical experience and how you can contribute to our team.
Communicate Clearly: When writing your application, keep it clear and concise. Remember, we need to see that you can communicate complex technical information effectively. Use straightforward language to explain your achievements and experiences.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you’re considered for the role. Don’t miss out on this opportunity to join our innovative team!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your AI Stuff
Make sure you brush up on the latest AI techniques, especially in NLP and Computer Vision. Be ready to discuss your hands-on experience with machine learning models and how you've applied them in real-world scenarios. This is your chance to showcase your technical expertise!
✨Showcase Your Collaboration Skills
Since this role involves working closely with software engineering teams and other stakeholders, be prepared to share examples of how you've successfully collaborated in the past. Highlight any projects where you’ve designed and deployed ML services, and how you communicated complex ideas to non-technical audiences.
✨Demonstrate Your Problem-Solving Abilities
Think of specific challenges you've faced in your previous roles and how you overcame them using statistical and machine learning techniques. This will show your analytical skills and ability to innovate, which are crucial for optimising business decisions.
✨Prepare Questions About Their Tech Stack
Research JPMorgan's tech stack and be ready to ask insightful questions about their MLOps tooling, big data technologies, and production architectures. This not only shows your interest in the role but also your proactive approach to understanding how you can contribute effectively.
