Machine Learning Scientist - Natural Language jobs at Jpmorgan in United States, Seattle

DESCRIPTION:

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Applied Statistics, Mathematics, Operations Research, Optimization, Data Science, or related field of study plus 3 years (36 months) of experience in the job offered or as Applied Artificial Intelligence / Machine Learning, Machine Learning Engineer, Research Scientist, or related occupation. The employer will alternatively accept a PhD in Applied Statistics, Mathematics, Operations Research, Optimization, Data Science, or related field of study plus 1 year (12 months) of experience in the job offered or as Applied Artificial Intelligence / Machine Learning, Machine Learning Engineer, Research Scientist, or related occupation.

Skills Required: This position requires experience with the following: At least one of the following: personalization, recommendation, speech recognition, or NLP; designing machine learning experiments and frameworks including feature extraction, data augmentation, synthetic data generation, model pre- training, fine-tuning, performance evaluation, robustness testing, interpretability analysis and visualization; outlining and evaluating intrinsic and extrinsic metrics for model performance aligned with business goals; big data and scalable model training; personalized contents, recommender systems, search, and ranking; A/B testing experimentation and data-driven product development; cloud-native deployment in a large scale distributed environment; experience in either: reinforcement Learning or Meta Learning; developing and debugging production-quality code; continuous integration models and unit test development; machine learning and deep learning toolkits including NLTK, spaCy, Hugging Face transformers, Scikit-Learn, Rasa NLU, PyTorch, Docker, Numpy, Pandas, Spark, MongoDB, Scala; experience with machine learning and deep learning.

Job Location: 1201 3rd Ave, Seattle, WA 98101.

Full-Time. Salary: $210,000 - $260,000 per year.

that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly

As an Executive Director on the Machine Learning Center of Excellence (MLCOE) team, you will be responsible for applying advanced machine learning techniques to a variety of complex tasks. These tasks include natural language processing, speech analytics, time series, reinforcement learning, and recommendation systems. You will work closely with different teams and actively contribute to our knowledge sharing community.

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 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

Required qualifications, capabilities, and skills

• 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.
• 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
• Strong publication record in Natural Language Processing, Machine Learning, Deep Learning or Reinforcement Learning at major conferences or journals