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Natural Language Processing Engineer Jobs (NOW HIRING)

... natural language processing solutions with measurable outcomes in production. * Strong programming skills in Python and experience using modern machine learning frameworks such as PyTorch or ...

Required : • 5+ years of hands-on experience as a machine learning engineer or data scientist with at least 2 years focused on Natural Language Processing • Bachelor's Degree or higher in one of ...

Machine learning, natural language processing, learning-to-rank, online learning, deep learning ... Strong programming skills in Python and Scala required. Experience in other programming languages ...

Machine learning, natural language processing, learning-to-rank, online learning, deep learning ... Strong programming skills in Python and Scala required. Experience in other programming languages ...

$77K - $105K/yr

Engineering About the Role We are seeking an exceptional Senior Machine Learning Engineer to join ... on Natural Language Processing applications and robust MLOps practices. The ideal candidate will ...

NY · On-site

AI Developer As an Artificial Intelligence (AI) Developer, you will be responsible for designing ... Natural Language Processing (NLP) and Computer Vision: * Implement NLP techniques for text analysis ...

LLM Research Engineer

Mountain View, CA · On-site

$90 - $121.86/hr

Conduct research on cutting-edge techniques in natural language processing (NLP) and machine ... Strong programming skills. * Proficiency with deep learning frameworks such as TensorFlow, PyTorch ...

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Natural Language Processing Engineer information

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$49.5K

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$142.5K

How much do natural language processing engineer jobs pay per year?

As of Sep 14, 2026, the average yearly pay for natural language processing engineer in the United States is $92,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,500.00 and $103,000.00 per year, depending on experience, location, and employer.

What does a natural language processing engineer do?

A Natural Language Processing (NLP) Engineer develops algorithms and models that enable machines to understand, interpret, and generate human language. They work with large datasets, train machine learning models, and fine-tune language models for applications like chatbots, speech recognition, and text analysis. NLP Engineers typically use programming languages like Python and frameworks such as TensorFlow, PyTorch, or spaCy. Their work involves data preprocessing, model training, and optimizing performance to enhance the accuracy and efficiency of language-based AI systems.

What does a typical day look like for a natural language processing engineer?

A typical day for a Natural Language Processing Engineer involves developing, testing, and refining language models and algorithms, often using real-world datasets. You might collaborate with data scientists, product managers, and software engineers to integrate NLP solutions into applications or address complex language-related challenges. Regular responsibilities include data preprocessing, feature engineering, model evaluation, and troubleshooting performance issues. Most NLP engineers work in a team-oriented, agile environment where clear communication and iterative development are key. This structure offers a dynamic workflow and opportunities to learn from others while making a tangible impact on the products you help build.

What are the key skills and qualifications needed to thrive as a natural language processing engineer?

To thrive as a Natural Language Processing Engineer, you need strong programming skills (especially in Python), a solid understanding of machine learning and linguistics, and typically a degree in computer science, computational linguistics, or a related field. Familiarity with NLP libraries such as NLTK, spaCy, TensorFlow, or PyTorch as well as experience with cloud platforms and version control is often required. Analytical thinking, collaboration, and effective communication are important soft skills in this role. These competencies ensure the ability to build robust language models, contribute to innovative projects, and work efficiently in dynamic, cross-functional teams.

Are natural language processing engineers in demand?

Natural Language Processing (NLP) engineers are in high demand due to the growing use of AI and machine learning in industries such as technology, healthcare, and finance. They often require skills in programming, machine learning frameworks, and understanding of linguistics, with job growth expected to continue as AI applications expand.
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Infographic showing various Natural Language Processing Engineer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, 1% Temporary, and 4% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $92,018 per year, or $44.2 per hour.

Applied AI/ML Lead - Payments

Seattle, WA • On-site

JPMorgan Chase & Co
Finance and Insurance • 10K+ employees

Full-time

Medical, Retirement

Re-posted 6 days ago


JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz


Job description

Are you passionate about harnessing the power of artificial intelligence and machine learning to solve real-world challenges? At JPMorganChase, we're transforming the way payments work in the Commercial & Investment Bank by leveraging cutting-edge document extraction and natural language processing (NLP) technologies. As a Vice President and Applied AI/ML Lead, you'll play a pivotal role in building innovative solutions that enhance trust, safety, and operational efficiency for one of the world's leading financial institutions.

As a Vice President, Applied AI and Machine Learning Lead at JPMorganChase within Payments Technology in the Commercial & Investment Bank, you will lead the delivery of document extraction and natural language processing capabilities that improve trust, safety, and operational effectiveness. You will own solutions end-to-end, from problem framing and data strategy to production deployment and measurement. You will remain hands-on while setting technical direction and partnering across product, engineering, data, risk, and compliance stakeholders.

Job Responsibilities

  • Own end-to-end delivery of document extraction and natural language processing solutions, from opportunity sizing and requirements through production rollout and iteration.
  • Design scalable model pipelines for document ingestion, text extraction, classification, and ranking, balancing accuracy, latency, throughput, and cost.
  • Develop and improve natural language processing algorithms and model approaches to extract entities, relationships, and signals from unstructured text and documents.
  • Define evaluation strategies and success metrics, including offline validation, error analysis, robustness testing, and controlled online measurement where appropriate.
  • Establish model lifecycle practices including reproducibility, testing, monitoring, drift detection, and incident response to sustain reliable production performance.
  • Partner with risk and compliance stakeholders to ensure appropriate documentation, controls, explainability expectations, and audit-ready processes.
  • Drive technical decisions through design reviews, code and model reviews, and pragmatic standards that raise quality and delivery velocity.
  • Communicate tradeoffs and recommendations to senior stakeholders, translating model behavior into decision-ready business impact.

Required Qualifications, Capabilities, and Skills

  • Formal training or certification on applied artificial intelligence and machine learning concepts and 5+ years applied experience
  • 5+ years of experience building and delivering applied machine learning or natural language processing solutions with measurable outcomes in production.
  • Strong programming skills in Python and experience using modern machine learning frameworks such as PyTorch or TensorFlow.
  • Hands-on experience with document extraction and natural language processing techniques including text classification and information extraction.
  • Experience designing data-driven solutions using SQL and distributed processing tools such as Spark or equivalent.
  • Experience deploying and operating machine learning services or pipelines in a cloud environment such as Amazon Web Services (or equivalent).
  • Demonstrated ability to translate ambiguous business problems into structured machine learning plans, including data strategy, evaluation, rollout, and operationalization.
  • Strong communication and collaboration skills, including the ability to explain technical tradeoffs to technical and non-technical partners.

Preferred Qualifications, Capabilities, and Skills

  • Experience with optical character recognition and document understanding workflows for scanned or semi-structured documents.
  • Experience with modern natural language processing architectures such as transformer-based models and techniques for optimization and efficient inference.
  • Experience with machine learning operations practices and tooling, including model registries, continuous integration and delivery for machine learning, and observability.
  • Experience with real-time or event-driven architectures supporting low-latency inference and feature generation.
  • Experience applying document extraction or natural language processing in payments, financial services, or regulated environments.

FEDERAL DEPOSIT INSURANCE ACT: This position is subject to Section 19 of the Federal Deposit Insurance Act. As such, an employment offer for this position is contingent on JPMorganChase's review of criminal conviction history, including pretrial diversions or program entries.

#LI-RB3

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We 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

J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. 

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