Applied AI ML - Sr. Associate - Machine Learning Scientist

Applied AI ML - Sr. Associate - Machine Learning Scientist

Full-Time 60000 - 80000 £ / year (est.) No working from home possible
JPMorgan Chase

At a Glance

  • Tasks: Join a leading team to optimise business decisions using cutting-edge AI techniques.
  • Company: JPMorgan Corporate Investment Bank, a pioneer in financial services innovation.
  • Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
  • Other info: Collaborative environment with potential for management roles based on experience.
  • Why this job: Make a real impact by advancing AI in finance and automating key processes.
  • Qualifications: PhD in a quantitative field and hands-on experience in AI and machine learning.

The predicted salary is between 60000 - 80000 £ per year.

As an Applied AI ML - Sr. Associate - Machine Learning Scientist in the JPMorgan Corporate Investment Bank, you will be part of our industry-leading team, 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 to build products that automate processes, help experts prioritize their time, and make better decisions. Our scientists take the lead in translating business requirements into machine learning problems and ensure through ongoing literature review that our solutions leverage the most appropriate algorithms. 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

  • Focus on rapidly delivering business value with our Applied AI ML solutions.
  • Collaborate closely with ML engineers throughout the entire product lifecycle to ensure that experimental results are reproducible and we’re able to rapidly promote from “Proof of Concept” to production.

Required Qualifications

  • Hands on experience in a commercial/ Postdoctoral Research role.
  • PhD in a quantitative discipline, e.g. Computer Science, Mathematics, Statistics.
  • Able to understand business objectives and align ML problem definition.
  • Track record of solving real world problems with AI.
  • Deep specialism in NLP or Computer Vision.
  • Deep understanding of fundamentals of statistics, optimization and ML theory.
  • Extensive experience with pytorch, numpy, pandas.
  • Hands on experience finetuning modern deep learning architectures (transformers, CNN, autoencoders etc.).
  • Knowledge of open source datasets and benchmarks in NLP or Computer Vision.
  • Able to communicate technical information and ideas at all levels; convey information clearly and create trust with stakeholders.
  • Experience working collaboratively within a team to build software.

Preferred Qualifications

  • Experience pretraining foundation models (LLM / vision/ multimodal).
  • Experience of documenting solutions for enterprise risk/ governance purposes.
  • Experience designing/ implementing pipelines using DAGs (e.g. Kubeflow, DVC, Ray).
  • Hands-on experience in implementing distributed/multi-threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.).
  • Experience of big data technologies (e.g. Spark, Hadoop).
  • Broad knowledge of MLOps tooling for versioning, reproducibility, observability etc.

Equal Employment Opportunity Statement

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.

Applied AI ML - Sr. Associate - Machine Learning Scientist employer: JPMorgan Chase

At JPMorgan Corporate Investment Bank, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. Our commitment to employee growth is evident through opportunities for advancement in cutting-edge AI applications within the financial sector, alongside a strong emphasis on diversity and inclusion. Located in a vibrant city, our team enjoys access to industry-leading resources and a supportive environment that encourages meaningful contributions to transformative projects.

JPMorgan Chase

Contact Details:

JPMorgan Chase Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Applied AI ML - Sr. Associate - Machine Learning Scientist

Tip Number 1

Network like a pro! Reach out to folks in the industry, especially those at JPMorgan. A friendly chat can open doors and give you insights that a job description just can't.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects in NLP or Computer Vision. This is your chance to demonstrate how you've tackled real-world problems with AI.

Tip Number 3

Prepare for interviews by brushing up on your ML theory and algorithms. Be ready to discuss how you can align machine learning solutions with business objectives—this is key!

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, it shows you're serious about joining our team.

We think you need these skills to ace Applied AI ML - Sr. Associate - Machine Learning Scientist

Natural Language Processing (NLP)
Computer Vision
Statistical Machine Learning
Pytorch
Numpy
Pandas
Deep Learning Architectures (Transformers, CNN, Autoencoders)

Some tips for your application 🫡

Tailor Your CV:Make sure your CV is tailored to the role of Applied AI ML - Sr. Associate. Highlight your hands-on experience with machine learning, especially in NLP or Computer Vision, and showcase any relevant projects that demonstrate your ability to solve real-world problems.

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in financial services and how your background aligns with the job requirements. Don’t forget to mention your collaborative spirit and how you can contribute to our team.

Showcase Your Technical Skills:Be sure to list your technical skills prominently, especially your experience with tools like PyTorch, NumPy, and Pandas. If you've worked with big data technologies or MLOps tooling, make that clear too – we love seeing those skills!

Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take the initiative to connect with us directly!

How to prepare for a job interview at JPMorgan Chase

Know Your AI Stuff

Make sure you brush up on the latest trends in AI, especially in Natural Language Processing and Computer Vision. Be ready to discuss your hands-on experience with tools like PyTorch and how you've applied them to solve real-world problems.

Align with Business Goals

Understand the business objectives of the role and be prepared to explain how you can translate those into machine learning problems. Show that you can think beyond the technical aspects and connect your work to the company's goals.

Collaborate Like a Pro

Since this role involves working closely with ML engineers, highlight your teamwork skills. Share examples of past collaborations where you contributed to building software and ensured reproducibility of results.

Communicate Clearly

Practice explaining complex technical concepts in simple terms. You’ll need to convey information clearly to stakeholders at all levels, so think of ways to build trust through effective communication during your interview.