NLP / LLM Scientist - Applied AI ML Lead - Machine Learning Centre of ExcellenceThe Machine Learning Centre 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 a highly collaborative environment with business, technologists and control partners to deploy solutions into production, and have a strong passion for machine learning, with time invested in learning, researching and experimenting with new innovations in the field. The candidate should have solid expertise in deep learning with hands-on implementation experience and strong analytical thinking, motivation and curiosity.

Responsibilities

Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and knowledge sharing

Develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks such as NLP, speech recognition and analytics, time-series predictions or recommendation systems

Collaborate with partner teams (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

Solid background in NLP or speech recognition and analytics, personalization/recommendation, and hands-on experience with machine learning and deep learning methods

PhD in a quantitative discipline (e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, Data Science) with relevant industry experience; or an MS with significant industry or research experience

Extensive experience with ML/DL toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)

Ability to design experiments and training frameworks, and to define and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals

Experience with big data and scalable model training; strong written and spoken communication to convey technical concepts to technical and business audiences

Scientific thinking with the ability to invent and work both independently and in collaborative teams

Curious, hardworking, detail-oriented, and motivated by complex analytical problems

Preferred Qualifications, Capabilities, And Skills

Strong background in Mathematics and Statistics; familiarity with financial services, CI 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 large-scale distributed environments; ability to develop and debug production-quality code

Published research in ML, Deep Learning or Reinforcement Learning at major conference or journal

About MLCOEThe Machine Learning Centre of Excellence (MLCOE) team partners across the firm to create and share ML solutions for challenging business problems. In this role you will work with a multi-disciplinary team focused exclusively on machine learning, using techniques such as deep learning and reinforcement learning.

For more information about the MLCOE, please visit mlcoe

To learn about how we\''re using AI/ML to drive transformational change, please read the JPMorgan technology blog

About UsJ.P. Morgan is a global leader in financial services, providing strategic advice and products to corporations, governments, wealthy individuals and institutional investors. We are an equal opportunity employer and place a high value on diversity and inclusion. We do not discriminate on the basis of protected attributes. 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 information about requesting an accommodation.

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