DESCRIPTION:
Duties: Design and develop automation-based systems for data analysis, document management, and client intelligence. Research machine learning methods for data processing and analysis. Develop machine learning models to solve real-world problems and apply it to tasks such as Natural Language Processing, speech recognition, time-series predictions, reinforcement learning, and recommendation systems. Collaborate with multiple partner teams to deploy solutions into production. Develop large-scale frameworks to accelerate the application of machine learning models across different areas of the business.
QUALIFICATIONS:
Minimum education and experience required: Master's degree in Computational Data Science, Computer Science, Electrical Engineering, Mathematics, Operations Research, or Data Science or related field of study plus 1 year of experience in the job offered or as Applied AI ML, Software Engineer, Analyst in Engineering Division, Research and Development Team, or related occupation.
Skills Required: This position requires experience with the following: Developing and deploying production-ready NLP and speech recognition systems; Designing and developing machine learning experiments and frameworks, including data ingestion, augmentation, generation, feature extraction, end-to-end model training, fine-tuning, performance evaluation and monitoring, robustness and integration testing, A/B testing, interpretability analysis, and visualization; Outlining and evaluating intrinsic and extrinsic model performance metrics aligned with business goals, including deriving extrinsic KPIs incorporating cost per model and cost savings from automation; Preparing and analyzing data quality metrics, including completeness and consistency; Using distributed deep learning, data processing, and model training frameworks, including PyTorch, TensorFlow, HuggingFace, Keras, SKlearn, NLTK, spaCy, Rasa NLU, Numpy, Pandas, and Spark; Processing large datasets, training scalable models, and deploying models on multiple CPUs and GPUs using Cloud-Native Managed Services including as AWS, Azure, and GCP; Applying machine learning techniques, including logistic regression, gradient-boosted trees, and deep learning approaches including RNN and CNN to NLP and Speech applications; Employing Elasticsearch inverted-index, BM25 ranking, and custom analyzers; Leveraging pretrained Transformer encoders including BERT, Sentence-Transformers, and spaCy for text understanding and extraction; Performing A/B testing and data-driven product development, including hypothesis and metrics design, randomization, statistical testing, multiple comparisons, error controls, and experiment monitoring; Implementing continuous integration for ML models, including pipeline definition and triggering using Jenkins, GitLab CI/CD, GitHub Actions; Artifact packaging, containerizing and deployment using Docker; Developing unit tests for ML, including module-level test cases, edge-case and invariant tests, coverage and static analysis, and test parameterization and fixtures; Automating hyperparameter searches using TensorFlow, PyTorch, and Keras; Tracking training runs and metrics using TensorBoard.
Job Location: 3203 Hanover St, Palo Alto, CA 94304.
Full-Time. Salary: $215,000 - $260,000 per year.
About UsWe offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of 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 & Co. is an Equal Opportunity Employer, including Disability/Veterans
Skills Required
- Master's degree in Computational Data Science, Computer Science, Electrical Engineering, Mathematics, Operations Research, Data Science, or a related field
- At least 1 year of experience in the job offered or as an Applied AI/ML professional, Software Engineer, Analyst in an Engineering Division, Research and Development Team member, or related occupation
- Experience developing and deploying production-ready NLP and speech recognition systems
- Experience designing machine learning experiments and frameworks, including data ingestion, augmentation, feature extraction, model training, evaluation, monitoring, testing, A/B testing, interpretability, and visualization
- Experience evaluating model performance metrics and business KPIs, including automation costs and savings
- Experience preparing and analyzing data quality metrics, including completeness and consistency
- Experience using PyTorch, TensorFlow, HuggingFace, Keras, scikit-learn, NLTK, spaCy, Rasa NLU, NumPy, Pandas, and Spark
- Experience processing large datasets, training scalable models, and deploying models on CPUs and GPUs using AWS, Azure, and GCP managed services
- Experience applying logistic regression, gradient-boosted trees, RNNs, CNNs, and deep learning to NLP and speech applications
- Experience with Elasticsearch inverted indexes, BM25 ranking, and custom analyzers
- Experience using pretrained Transformer encoders, including BERT and Sentence-Transformers
- Experience with data-driven product experimentation, statistical testing, randomization, multiple-comparison controls, and experiment monitoring
- Experience implementing continuous integration for machine learning models using Jenkins, GitLab CI/CD, or GitHub Actions
- Experience packaging artifacts, containerizing applications, and deploying with Docker
- Experience developing unit tests for machine learning systems, including edge-case, invariant, coverage, static-analysis, parameterization, and fixture testing
- Experience automating hyperparameter searches with TensorFlow, PyTorch, and Keras
- Experience tracking training runs and metrics using TensorBoard
JPMorganChase Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JPMorganChase and has not been reviewed or approved by JPMorganChase.
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Healthcare Strength — Medical, dental, vision, and mental-health coverage are broad, with wellness incentives, on-site or virtual care, and an EAP offering coaching and counseling. Plan materials emphasize accessible options, including multiple medical choices and tools to manage costs.
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Parental & Family Support — Paid parental leave extends up to 16 weeks for all parents, supplemented by paid Critical Caregiver Leave. Family resources include backup childcare via Bright Horizons, lactation support and milk-shipping, family-building assistance, and even a free five-month SNOO rental for newborns.
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Retirement Support — Retirement programs include a 401(k) with an annual company match and automatic pay credits for most employees, with a legacy pension available to earlier hires. An Employee Stock Purchase Plan at a 5% discount further supports long-term savings.
JPMorganChase Insights
What We Do
JPMorgan Chase & Co. (NYSE: JPM) is a leading global financial services firm with assets of $3.7 trillion and operations worldwide. The firm is a leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management. A component of the Dow Jones Industrial Average, JPMorgan Chase & Co. serves millions of consumers in the United States and many of the world’s most prominent corporate, institutional and government clients under its J.P. Morgan and Chase brands. Technology fuels every aspect of our company and is at the heart of everything we do. With over 50,000 technologists globally and an annual tech spend of $12 billion, we are dedicated to improving the design, analytics, development, coding, testing and application programming that goes into creating high quality software and new products. Learn more about technology at our firm, explore resources from our Distinguished Engineers, AI & ML researchers, and other experts; access the latest episode of our TechTrends podcast, and more at www.jpmorgan.com/technology. Information about JPMorgan Chase & Co. is available at www.jpmorganchase.com. ©2023 JPMorgan Chase & Co. All rights reserved. JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans.
Why Work With Us
Our technologists work on a diverse range of solutions that include strategic technology initiatives, big data, mobile, electronic payments, machine learning, cybersecurity, enterprise cloud development, and other state-of-the-art technologies.
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