Natural Language Processing Jobs
Natural Language Processing jobs are open across technology, healthcare, finance, and media, from new-grad NLP engineer to principal research scientist, with specializations in conversational AI, text classification, and machine translation. See the openings below and apply to the ones that match your experience.
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See related jobsAt JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data & Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. 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.
As a Machine Learning Scientist – Natural Language Processing (NLP) - Vice President in the Machine Learning Center of Excellence, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.
Job responsibilities
- Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
- Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
- Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
- Lead 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 3 years of experience OR an MS with at least 5 years of industry or research experience in the field
- Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and 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
- 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
Preferred qualifications, capabilities, and skills
- Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
- Knowledge in search/ranking 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 or Deep Learning at a major conference or journal
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.
#MLCOE_jobs
#CDAO_CAO_jobs
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
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
At JPMorgan Chase, AI and technology promote our global operations with unmatched scale and speed. We invest over $18 billion annually in innovation, data leverage, and security to shape the future for our clients, communities, and employees. The Chief Data & Analytics Office (CDAO) accelerates our data and analytics journey, with the Machine Learning Center of Excellence (MLCOE) creating and deploying solutions for complex business challenges. By ensuring data quality and leveraging insights, the CDAO supports our commercial goals, enhancing productivity and risk management through AI and machine learning. 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.
As a Machine Learning Scientist – Natural Language Processing (NLP) - Vice President in the Machine Learning Center of Excellence, you will own the full lifecycle of developing and deploying machine learning solutions, from ideation to production. Acting as a leading voice within JPMC on all things Generative AI (GenAI), you will partner closely with all lines of business to innovate new solutions that drive transformational change for the bank. You will actively participate in our knowledge sharing community, representing your work inside and outside of the firm at leading industry conferences amongst peers and leaders in the space. We seek someone who excels in a highly collaborative, fast-paced environment, and holds a strong passion for machine learning to make a significant impact at a leading global financial institution.
Job responsibilities
- Research and develop state-of-the-art machine learning models to solve real-world problems and apply them to tasks involving Generative AI (GenAI)
- Act as a thought partner for JPMC leaders and help the business identify and implement new machine learning methods that deliver impact
- Drive cross-functional collaboration with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy, and Business Management to deploy solutions into production
- Lead 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 3 years of experience OR an MS with at least 5 years of industry or research experience in the field
- Solid background in Generative AI (GenAI) and hands-on experience and solid understanding of machine learning and deep learning methods and 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
- 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
Preferred qualifications, capabilities, and skills
- Strong background in Mathematics and Statistics; Familiarity with the financial services industries and continuous integration models and unit test development
- Knowledge in search/ranking 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 or Deep Learning at a major conference or journal
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.
#MLCOE_jobs
#CDAO_CAO_jobs
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
ABOUT THE TEAM
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.
Natural Language Processing Jobs by Experience Level
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Find JobsNatural Language Processing Job Market
Who's Hiring
Top Industries Hiring
- Fintech
- Banking & Financial Services
- Investment & Asset Management
What Employers Look For
The qualifications that appear most often in natural language processing jobs.
- Proficiency in Python with hands-on experience using PyTorch or TensorFlow for model development
- Experience fine-tuning or deploying large language models such as BERT, GPT, or T5 variants
- Strong foundation in linguistics, tokenization, parsing, and text preprocessing techniques
- Familiarity with cloud platforms and ML infrastructure for training and serving NLP models at scale
- Bachelor's or master's degree in computer science, computational linguistics, or a related technical field
- Experience evaluating model performance using standard NLP benchmarks and metrics such as F1 and BLEU
Tips for Your Natural Language Processing Job Search
Tailor your resume to model types
Specify which architectures you've worked with, whether transformer-based models, sequence-to-sequence systems, or retrieval-augmented generation pipelines. Hiring managers scan for exact model families, not just 'deep learning experience,' so name them explicitly in each application.
Build a public GitHub with reproducible experiments
Recruiters and hiring teams for NLP roles almost always check GitHub. Publish notebooks that show data preprocessing, fine-tuning steps, and evaluation metrics. A well-documented repo on a domain-specific dataset demonstrates applied skill faster than any resume line.
Apply early to roles that fit
Migrate Mate lists natural language processing openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter by domain before searching titles
NLP roles in clinical documentation differ sharply from those in customer support automation or legal contract analysis. Decide which domain aligns with your training data experience first, then search within that vertical to avoid wasting applications on mismatched stacks.
Prepare a live demo for technical screens
Many NLP interview loops include a take-home or live coding segment where you parse, tokenize, and evaluate a dataset on the spot. Practice explaining your tokenization choices and handling edge cases like out-of-vocabulary terms under time pressure before the interview.
Negotiate around compute access, not just salary
For NLP roles, GPU quota, cloud credits, and access to proprietary datasets directly affect your ability to ship work. Ask about infrastructure budget and model deployment ownership during offer discussions, since these shape your day-to-day productivity as much as compensation.
Natural Language Processing Jobs: Frequently Asked Questions
Which companies are hiring the most natural language processings?
The companies hiring the most natural language processings right now include JPMorganChase, Amazon, and Guidehouse, with the largest share of openings in Washington, California, and Maryland, based on current listings on Migrate Mate as of September 2026. Demand is concentrated in technology, healthcare AI, and financial services.
How many natural language processing jobs are remote?
About 0% of natural language processing openings are fully remote or hybrid as of September 2026, reflecting strong employer flexibility for research and engineering roles. Positions focused on model research and data annotation tend to offer the highest share of fully remote arrangements, while production engineering roles more often require some on-site presence.
How do you become a natural language processing?
Start by building a strong foundation in Python, linear algebra, and probability, then work through core NLP concepts including tokenization, embeddings, and sequence modeling. Fine-tune a pretrained transformer on a public dataset and publish your results. Formal education in computer science or computational linguistics helps, but a documented project portfolio and contributions to open-source NLP libraries carry significant weight with hiring teams.
How do you get hired in natural language processing with little experience?
Focus on a single, well-documented project that solves a concrete text problem, such as building a domain-specific named-entity recognizer or a sentiment classifier on a niche dataset. Apply to junior research engineer or NLP data analyst roles, which often have lower barriers than pure research positions. Contributing to open-source NLP libraries and sharing findings in public write-ups can substitute for formal industry experience.
What does the natural language processing interview process look like?
Most NLP interview loops begin with a recruiter screen followed by a technical phone interview covering Python, data structures, and basic ML concepts. A take-home assignment or live coding challenge typically involves preprocessing text, fine-tuning a model, and evaluating output quality. Final rounds usually include a research presentation or system design discussion where you explain architectural tradeoffs and walk through past project decisions with the engineering or science team.
Where can I find and apply to natural language processing jobs?
You can find and apply to natural language processing jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your background in model development, applied research, or NLP engineering, then apply directly to each listing that fits your experience and the domain you want to work in.
See All 5 Natural Language Processing Jobs
Find roles that match your experience and apply in just a few clicks.
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