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Applied AI ML opportunities are available at Sr. Associate, Vice President and Executive Director level in New York, Palo Alto and Seattle, WA locations. This role offers a unique opportunity to explore novel and complex challenges that could profoundly transform how the bank operates.
Machine Learning Scientist – NLP & Recommender Systems – Associate / Vice President / Executive Director
The Machine Learning Center of Excellence invites the successful candidate to apply sophisticated Machine Learning methods to a wide variety of complex tasks including natural language processing, speech analytics, Time Series, reinforcement learning and recommendation systems.
The candidate must excel in working in a highly collaborative environment together with the business, technologists and control partners to deploy solutions into production. The candidate must also have a strong passion for Machine Learning and invest independent time towards learning, researching and experimenting with new innovations in the field. The candidate must have solid expertise in Deep Learning with hands-on implementation experience and possess strong analytical thinking, a deep desire to learn and be highly motivated.
Job Responsibilities
- Research and explore new Machine Learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community
- Develop state-of-the art Machine Learning models to solve real-world problems and apply it to tasks such as NLP, speech recognition and analytics, time-series predictions or recommendation systems
- Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production
- Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of Machine Learning models across different areas of the business
Required qualifications, capabilities, and skills
- [ED]: PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science, with at least five years of industry or research experience in the field. Or an MS with at least eight years of experience; [VP]: 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; [Assoc]: MS in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science
- Solid background in NLP or speech recognition and analytics, personalization/recommendation and 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)
- 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 and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.
- Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments
- 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
Preferred qualifications, capabilities, and skills
- Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development
- Knowledge in search/ranking, Reinforcement Learning or Meta Learning
- Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code
- Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set, and location. For those in eligible roles, we offer discretionary incentive compensation which may be awarded in recognition of firm performance and individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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.
JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans
ABOUT THE TEAM
Our Corporate & Investment Bank relies on innovators like you to build and maintain the technology that helps us safely service the world’s important corporations, governments and institutions. You'll develop solutions that help the bank provide strategic advice, raise capital, manage risk, and extend liquidity in markets spanning over 100 countries around the world.
