At a Glance
- Tasks: Lead AI initiatives to transform business decisions and automate processes in finance.
- Company: Join J.P. Morgan, a global leader in financial services with a focus on innovation.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Why this job: Be at the forefront of AI technology and make a real impact in financial services.
- Qualifications: Experience in ML engineering and a strong background in quantitative disciplines required.
- Other info: Collaborative team culture with a commitment to diversity and inclusion.
The predicted salary is between 48000 - 72000 ÂŁ per year.
Take a technical leadership position within JPMorgan's Commercial & Investment Bank, where you'll harness cuttingâedge AI techniques to revolutionize business decisions and automate processes. As an Applied AI / ML Lead â Vice President - Machine Learning Engineer in the Applied AI ML team at JPMorgan Commercial & Investment Bank, you will be at the forefront of combining cuttingâedge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the stateâofâtheâart 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 AIâpowered products and services and increasing opportunity for reâuse 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 nonâtechnical 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.
- Masters degree or 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 â 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, optimisation and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders etc.).
- Extensive experience with pytorch, numpy, pandas.
- Handsâon experience in implementing distributed/multiâthreaded/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.
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 firstâclass business in a firstâclass way approach to serving clients drives everything we do. We strive to build trusted, longâterm 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 equalâopportunity 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, colour, 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.
About The Team 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.
Applied AI ML Lead - DocAI in London employer: JPMorganChase
Contact Detail:
JPMorganChase Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Applied AI ML Lead - DocAI in London
â¨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and ML. This is your chance to demonstrate your expertise and make a lasting impression on potential employers.
â¨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your past experiences in detail. Confidence is key!
â¨Tip Number 4
Don't forget to apply through our website! Itâs the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Applied AI ML Lead - DocAI in London
Some tips for your application đŤĄ
Tailor Your CV: Make sure your CV is tailored to the Applied AI ML Lead role. Highlight your experience with machine learning, especially in NLP and Computer Vision, and donât forget to showcase any relevant projects or achievements that align with what weâre looking for.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why youâre passionate about AI and how your skills can help us revolutionise business decisions at JPMorgan. Keep it concise but impactful!
Showcase Your Technical Skills: We want to see your technical prowess! Be sure to mention your hands-on experience with tools like PyTorch, and any MLOps tooling youâve used. Donât shy away from discussing your familiarity with big data technologies too!
Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. Itâs the easiest way for us to keep track of your application and ensure it gets to the right people!
How to prepare for a job interview at JPMorganChase
â¨Know Your AI Stuff
Make sure you brush up on the latest AI techniques, especially in Natural Language Processing 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.
â¨Showcase Your Collaboration Skills
This role involves working closely with software engineering teams and other stakeholders. Prepare examples of past collaborations where you successfully communicated complex technical concepts to non-technical audiences. Highlight how you built trust and worked towards common goals.
â¨Demonstrate Your Problem-Solving Mindset
Be ready to tackle hypothetical problems during the interview. Think about how you would approach building scalable data science capabilities or designing ML services. Show your thought process and how you leverage statistical and machine learning techniques to solve business challenges.
â¨Prepare for Technical Questions
Expect deep dives into your technical knowledge, especially around MLOps tooling and big data technologies. Brush up on your understanding of frameworks like Ray and Spark, and be prepared to discuss your experience with distributed applications and microservices.