Applied AI ML - Senior Associate - Machine Learning Engineer

JPMorgan Chase & Co.
London
1 month ago
Create job alert

Job Description

Join our team as a Sr. Associate Machine Learning Engineer to advance AI in financial services and optimize business decisions.

As a Senior Associate Machine Learning Engineer in the Applied AI ML team at JPMorgan Corporate Investment Bank, you'll be at the forefront of AI innovation, combining cutting-edge techniques with unique data assets to optimize business decisions and automate processes. This role offers a unique blend of scientific research and software engineering, allowing you to advance AI in financial services and build impactful products.

In this role, you will leverage the latest research in Natural Language Processing, Computer Vision, and statistical machine learning to build AI-powered products that automate processes and enhance decision-making. You will collaborate with software engineering teams to design scalable Machine Learning services and communicate AI capabilities to diverse audiences.

Job Responsibilities:

  1. Build robust Data Science capabilities scalable across multiple business use cases.
  2. Collaborate with software engineering teams to design and deploy Machine Learning services.
  3. Research and analyze data sets using statistical and machine learning techniques.
  4. Communicate AI capabilities and results to both technical and non-technical audiences.
  5. Document approaches, techniques, and processes to comply with industry regulations.
  6. Collaborate with cloud and SRE teams in designing and delivering production architectures.

Required Qualifications, Capabilities, and Skills:

  1. Hands-on experience in an ML engineering role.
  2. PhD in a quantitative discipline, e.g., Computer Science, Mathematics, Statistics.
  3. Track record of developing and deploying business-critical machine learning models.
  4. Broad knowledge of MLOps tooling for versioning, reproducibility, and observability.
  5. Experience monitoring and maintaining models over time.
  6. Specialism in NLP or Computer Vision.
  7. Solid understanding of statistics, optimization, and ML theory.
  8. Extensive experience with PyTorch, NumPy, and Pandas.
  9. Familiarity with deep learning architectures (e.g., transformers, CNN, autoencoders).
  10. Excellent grasp of computer science fundamentals and development best practices.
  11. Ability to communicate technical information clearly and build trust with stakeholders.

Preferred Qualifications, Capabilities, and Skills:

  1. Experience designing/implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray).
  2. Experience with big data technologies (e.g., Spark, Hadoop).
  3. Hands-on experience with distributed/multi-threaded/scalable applications.
  4. Knowledge of open-source datasets and benchmarks in NLP/Computer Vision.
  5. Experience constructing batch and streaming microservices exposed as REST/gRPC endpoints.
  6. 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, 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

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.

#J-18808-Ljbffr

Related Jobs

View all jobs

Sr. Director of Engineering, AI & ML

Research Scientist: AI for Quantum Chemistry

Research Scientist: AI for Quantum Chemistry

Machine Learning (ML) Engineer II

Lead AI/ML Engineer

ML (Machine Learning) Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

Careers

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.

Jobs Careers

10 Essential Books to Read to Nail Your Data Science Career in the UK

Data science continues to be one of the most exciting and rapidly evolving fields in tech. With industries across the UK—ranging from finance and healthcare to e-commerce and government—embracing data-driven decision-making, the demand for skilled data scientists has soared. Whether you're a recent graduate looking for your first role or a professional aiming to advance your career, staying updated through books is crucial. In this article, we explore ten essential books every data science job seeker in the UK should read. Each book provides valuable insights into core concepts, practical applications, and industry-standard tools, helping you build skills employers are actively looking for.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.