**Company: Aumni Job Description Summary: The Machine Learning Center of Excellence is looking for a Senior Associate to apply machine learning methods to tasks like natural language processing, speech analytics, and recommendation systems. The candidate must have expertise in Deep Learning, be highly collaborative, and have a strong passion for machine learning. Responsibilities include research, developing machine learning models, collaborating with partner teams, and driving firm-wide initiatives. Required qualifications include a background in NLP or speech recognition, a PhD in a quantitative discipline, and experience with machine learning tools. The Machine Learning Center of Excellence partners across the firm to create machine learning solutions for challenging business problems. The Chief Data & Analytics Office at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey and harnessing AI and ML technologies. Job Description: Job Description NLP / LLM Scientist - Applied AI ML Senior Associate - Machine Learning Centre of Excellence 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 practiced 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 • 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 • PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science with reasonable industry experience, or an MS with industry or research experience in the field • Applied 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 About MLCOE The Machine Learning Center of Excellence (MCLOE) team partners across the firm to create and share Machine Learning Solutions for our most challenging business problems. In this role you will work and collaborate with a team comprised of a multi-disciplinary community of experts focused exclusively on Machine Learning. On this team you will work with cutting-edge techniques in disciplines such as Deep Learning and Reinforcement Learning For more information about the MLCOE, please visit http://www.jpmorgan.com/mlcoe. To learn about how we’re using AI/ML to drive transformational change, please read this blog: https://www.jpmorgan.com/insights/technology/technology-blog?source=cib_di_jp_aBtechblog102 The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company’s data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions 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
Company:Aumni
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Level of experience (years):Senior (5+ years of experience)
“Fine-tuning” means adapting an existing machine learning model for specific tasks or use cases. In this post I’m going to walk you through how you can fine tune a large language model for sentence similarity using some hand annotated test data. This example is in the psychology domain. You need training data consisting of pairs of sentences, and a “ground truth” of how similar you want those sentences to be when you train your custom sentence similarity model.
Hire an NLP developer and untangle the power of natural language in your projects The world is buzzing with the possibilities of natural language processing (NLP). From chatbots that understand your needs to algorithms that analyse mountains of text data, NLP is revolutionising industries across the board. But harnessing this power requires the right expertise. That’s where finding the perfect NLP developer comes in. Post a job in NLP on naturallanguageprocessing.
Natural language processing What is natural language processing? Natural language processing, or NLP, is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language. NLP is a branch of AI but is really a mixture of disciplines such as linguistics, computer science, and engineering. There are a number of approaches to NLP, ranging from rule-based modelling of human language to statistical methods. Common uses of NLP include speech recognition systems, the voice assistants available on smartphones, and chatbots.