Applied AI ML Lead - DocAI
Applied AI ML Lead - DocAI

Applied AI ML Lead - DocAI

Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead AI initiatives to transform business decisions and automate processes at JPMorgan.
  • Company: Join a global leader in financial services with a commitment to innovation.
  • Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
  • Why this job: Be at the forefront of AI technology in finance and make a real impact.
  • Qualifications: Experience in ML engineering and a strong academic background in quantitative disciplines.
  • Other info: Collaborative team culture with a focus on diversity and inclusion.

The predicted salary is between 36000 - 60000 ÂŁ 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.
  • 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 – 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.
  • 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.

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, 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 employer: JPMorganChase

J.P. Morgan is an exceptional employer, offering a dynamic work environment where innovation meets collaboration. As part of the Applied AI ML team, you will engage with cutting-edge technologies in a culture that values diversity and inclusion, while also providing ample opportunities for professional growth and development. With a commitment to employee well-being and a focus on building long-term partnerships, J.P. Morgan empowers its employees to make meaningful contributions to the financial services industry.
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Contact Detail:

JPMorganChase Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Applied AI ML Lead - DocAI

✨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 related to 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 specific to AI and ML roles. We want you to feel confident and ready to impress!

✨Tip Number 4

Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who are proactive!

We think you need these skills to ace Applied AI ML Lead - DocAI

Machine Learning Engineering
Natural Language Processing (NLP)
Computer Vision
Statistical Analysis
MLOps Tooling
Deep Learning Architectures
PyTorch
NumPy
Pandas
Distributed Systems
Microservices Architecture
Data Pipeline Design
Big Data Technologies
REST/gRPC APIs
Communication Skills

Some tips for your application 🫡

Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the job description. Highlight your hands-on experience in ML engineering and any relevant projects you've worked on, especially those involving NLP or Computer Vision.

Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for the role. Don't forget to mention specific projects or achievements that showcase your expertise in machine learning.

Showcase Your Technical Skills: In your application, be sure to include details about your experience with MLOps tooling and any big data technologies you've worked with. We want to see your familiarity with frameworks like PyTorch, Spark, and others that are relevant to the role.

Apply Through Our Website: We encourage you to apply directly through our website. This ensures your application gets to the right people and helps us keep track of all candidates efficiently. Plus, it’s super easy!

How to prepare for a job interview at JPMorganChase

✨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.

✨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.

✨Demonstrate Your Problem-Solving Mindset

Be prepared to discuss specific challenges you've faced in ML engineering and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers and showcase your analytical skills and creativity in problem-solving.

✨Familiarise Yourself with MLOps Tools

Since MLOps is crucial for this position, make sure you know your way around tools like Kubeflow, DVC, and big data technologies like Spark. Be ready to explain how you've used these tools in previous projects to ensure model reproducibility and observability.

Applied AI ML Lead - DocAI
JPMorganChase
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