Job description
Create innovative machine learning solutions to solve business critical problems. Develop software and application system prototypes of the proposed solutions. Conduct experiments to evaluate the performance and effectiveness of the solutions. Create proof-of-concept technology demonstrations. Potentially generate creative solutions (patents) and publish research results internally and in some cases where permissible external events.
To be successful in this role, one most important requirements is the innate curiosity for what's new and a strong ability to learn new technologies quickly. The individual must possess deep, hands-on technical skills and be familiar with a wide range of technical themes and development practices. They will contribute as technical subject matter experts to the various machine learning projects, out-of-box thinking and team work is also critical for this role.
Responsibilities
- Research and explore new machine learning methods through independent study, attending industry-leading conferences and experimentation
- Develop state-of-the art machine learning models to solve real-world problems and apply it to complex business critical problems in Cybersecurity, Software and Technology Infrastructure
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
- Drive firmwide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business
- Contribute to reusable code and components that are shared internally and also externally
Minimum Qualifications
- PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science. Or an MS with at least three years of industry or research experience in the field.
- Hands-on experience and solid understanding of machine learning and deep learning methods
- Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
- Scientific thinking and the ability to invent
- Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals
- Experience with big data and scalable model training
- Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences
- Curious, hardworking and detail-oriented, and motivated by complex analytical problems
- Ability to work both independently and in highly collaborative team environments
Beneficial Skills
- Strong background in Mathematics and Statistics
- Familiarity with the financial services industries
- Experience with A/B experimentation and data/metric-driven product development
- Experience with cloud-native deployment in a large scale distributed environment
- Knowledge in Reinforcement Learning or Meta Learning
- Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
- Ability to develop and debug production-quality code
- Familiarity with continuous integration models and unit test development
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. In accordance with applicable law, we make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as any mental health or physical disability needs.