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hackajob · 1 week ago

Machine Learning Scientist - Natural Language Processing (NLP) - Sr Associate - Machine Learning Center of Excellence

New York, NY

Full-time

Onsite

Mid, Senior Level

$128K/yr - $195K/yr

3+ years exp

hackajob is collaborating with J.P. Morgan to connect them with exceptional tech professionals for this role. As a Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate, you will apply sophisticated machine learning methods to complex tasks and collaborate with various teams to deploy solutions into production.

Artificial Intelligence (AI)Generative AIHuman ResourcesRecruitingSoftware

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 natural language processing (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

Qualification

Natural Language ProcessingDeep LearningMachine LearningTensorFlowPyTorchBig DataAnalytical ThinkingCuriosityCollaborationCommunicationDetail-oriented

Required

PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 3 years of industry or research experience in the field

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

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