Nlp Engineer Jobs
Nlp Engineer jobs are open across tech, healthcare, finance, and media, from new-grad to principal and staff levels, with specializations in conversational AI, text classification, and information extraction. Find a role that fits from the openings below and apply directly.
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Showing 5 of 16+ Nlp Engineer jobs
INTRODUCTION
Interested in joining us to deliver the world’s most advanced silicon? At Apple, new ideas have a way of becoming phenomenal products very quickly. There's no telling what you could accomplish at Apple. The people who work here have reinvented entire industries with Apple silicon power all our products. The same real passion for innovation that goes into our products also applies to our practices - we continue to strengthen our commitment to leave the world better than we found it!
As a key member of our best-in-class CAD Group, you will be part of developing an analytic platform to identify and recommend solutions to signoff IR/EM analysis. You will have the opportunity to acquire a broad spectrum of knowledge spanning various disciplines and stages of silicon design, also applying machine learning (ML) and large language modeling (LLM) technologies to provide more accurate and efficient design feedback. These LLM applications encompass tasks such as large data summarization, information retrieval, triage, and chatbot development, alongside traditional silicon design areas such as static/dynamic IR analysis, signal/power grid extraction, STA timing, signal/power EM analysis, and signoff.
The successful candidate will excel in dynamic, collaborative working environments and exhibit a hands-on, enthusiastic, self-motivated approach, with a strong drive to succeed in challenging settings. If you are eager to tackle challenges with innovative solutions, deliver exceptional user experiences, and pay meticulous attention to detail, this role may be the perfect fit for you. As a member of our team, your contributions will directly impact the experiences of millions of Apple customers in delivering state of the art processors to the wide range of Apple products.
ROLE AND RESPONSIBILITIES
In this highly visible role, your primary responsibilities will include:
-
Developing innovative ML and large language model applications to understand, explain, and interact with EDA (electronic design automation) software. Designing and implementing their interaction with our extensive compute infrastructure.
-
Generating customized reports and dashboards to identify IR/EM issues and recommended solutions to improve power grid integrity.
-
Identifying opportunities to automate and streamline various IR/EM analysis and signoff flows.
-
Support and collaborate with design groups (Physical-design and integration, Circuit-design / Power / Package & System / Technology) on their IR/EM requirements for various analysis flows.
-
Work side by side with EDA vendors to enhance and develop solution to improve efficiency and capacity.
MINIMUM QUALIFICATIONS
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Experience in developing object-oriented programs, utilizing data structures, and writing algorithms.
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Experience in writing machine learning algorithms, implementing natural language processing (NLP), or using large language models in industry applications.
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Experience in EDA Tool, CAD flow or TFM (Tool Flow Methodology).
-
Proficiency with UNIX shell environment, Python, and code revision control.
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Minimum requirement of BS + 3 years of relevant industry experience.
PREFERRED QUALIFICATIONS
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Knowledge in some of the PNR implementation and/or EMIR analysis flow.
-
Experience in electrical engineering machine learning applications.
-
Experience with large language models, including fine-tuning, retrieval augmented generation, and prompt engineering.
-
Ability to coordinate and drive initiatives with little to no oversight.
-
Excellent communication and presentation skills.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
INTRODUCTION
Interested in joining us to deliver the world’s most advanced silicon? At Apple, new ideas have a way of becoming phenomenal products very quickly. There's no telling what you could accomplish at Apple. The people who work here have reinvented entire industries with Apple silicon power all our products. The same real passion for innovation that goes into our products also applies to our practices - we continue to strengthen our commitment to leave the world better than we found it!
As a key member of our best-in-class CAD Group, you will be part of developing an analytic platform to identify and recommend solutions to signoff IR/EM analysis. You will have the opportunity to acquire a broad spectrum of knowledge spanning various disciplines and stages of silicon design, also applying machine learning (ML) and large language modeling (LLM) technologies to provide more accurate and efficient design feedback. These LLM applications encompass tasks such as large data summarization, information retrieval, triage, and chatbot development, alongside traditional silicon design areas such as static/dynamic IR analysis, signal/power grid extraction, STA timing, signal/power EM analysis, and signoff.
The successful candidate will excel in dynamic, collaborative working environments and exhibit a hands-on, enthusiastic, self-motivated approach, with a strong drive to succeed in challenging settings. If you are eager to tackle challenges with innovative solutions, deliver exceptional user experiences, and pay meticulous attention to detail, this role may be the perfect fit for you. As a member of our team, your contributions will directly impact the experiences of millions of Apple customers in delivering state of the art processors to the wide range of Apple products.
ROLE AND RESPONSIBILITIES
In this highly visible role, your primary responsibilities will include:
-
Developing innovative ML and large language model applications to understand, explain, and interact with EDA (electronic design automation) software. Designing and implementing their interaction with our extensive compute infrastructure.
-
Generating customized reports and dashboards to identify IR/EM issues and recommended solutions to improve power grid integrity.
-
Identifying opportunities to automate and streamline various IR/EM analysis and signoff flows.
-
Support and collaborate with design groups (Physical-design and integration, Circuit-design / Power / Package & System / Technology) on their IR/EM requirements for various analysis flows.
-
Work side by side with EDA vendors to enhance and develop solution to improve efficiency and capacity.
MINIMUM QUALIFICATIONS
-
Experience in developing object-oriented programs, utilizing data structures, and writing algorithms.
-
Experience in writing machine learning algorithms, implementing natural language processing (NLP), or using large language models in industry applications.
-
Experience in EDA Tool, CAD flow or TFM (Tool Flow Methodology).
-
Proficiency with UNIX shell environment, Python, and code revision control.
-
Minimum requirement of BS + 3 years of relevant industry experience.
PREFERRED QUALIFICATIONS
-
Knowledge in some of the PNR implementation and/or EMIR analysis flow.
-
Experience in electrical engineering machine learning applications.
-
Experience with large language models, including fine-tuning, retrieval augmented generation, and prompt engineering.
-
Ability to coordinate and drive initiatives with little to no oversight.
-
Excellent communication and presentation skills.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Find Nlp Engineer JobsNlp Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Apple4
- Axle2
- Samsung Research America2
- Bloomberg1
- Davis Polk & Wardwell LLP1
Top Industries Hiring
- Electronics & Hardware4
- Technology & Software4
- Consulting & Professional Services3
- Investment & Asset Management3
- Banking & Financial Services2
What Employers Look For
The qualifications that appear most often in nlp engineer jobs.
- Proficiency in Python with hands-on experience in Hugging Face Transformers and PyTorch or TensorFlow
- Experience fine-tuning or pre-training large language models on domain-specific corpora
- Familiarity with NLP libraries including spaCy, NLTK, Gensim, or Stanford CoreNLP
- Strong background in text preprocessing, tokenization, embeddings, and vector similarity search
- Experience deploying NLP models to production using REST APIs or model-serving frameworks
- Bachelor's or master's degree in computer science, computational linguistics, or a related quantitative field
Tips for Your Nlp Engineer Job Search
Tailor your resume to model types
Hiring managers scan for the specific architectures you've worked with, whether that's transformer-based models, sequence-to-sequence, or large language models. Name the exact frameworks like spaCy, Hugging Face, or NLTK and the downstream tasks each project solved.
Showcase end-to-end production experience
Many nlp engineer candidates list model training but skip deployment. Highlight work where you took a model from experimentation through serving, including how you handled latency, drift, or data pipeline failures in a real product context.
Apply early to roles that fit
Migrate Mate lists nlp engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target job descriptions by task type
Filter openings by the core NLP task they emphasize, such as named-entity recognition, sentiment analysis, or machine translation. Applying to roles aligned with your strongest task domain puts your portfolio in direct context with what the team actually ships.
Prepare a system design answer for NLP pipelines
Technical interviews at most companies include a design round where you walk through how you'd build a full text-processing pipeline. Practice explaining your choices around tokenization, embedding strategy, model selection, and serving infrastructure out loud before the interview.
Negotiate with benchmark data in hand
Before an offer conversation, look up the Bureau of Labor Statistics occupational data for software and related roles in your target city, and cross-reference with publicly posted compensation bands when companies share them. Citing verified sources keeps negotiation grounded and professional.
Nlp Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most nlp engineers?
The companies hiring the most nlp engineers right now include Apple, Axle, and Samsung Research America, with the largest share of openings in Texas, New York, and California, based on current listings on Migrate Mate as of June 2026. Demand is particularly concentrated at companies building conversational AI, enterprise search, and healthcare documentation tools.
How many nlp engineer jobs are remote?
About 19% of nlp engineer openings are fully remote or hybrid as of June 2026, making it one of the more flexible roles in applied machine learning. Research and modeling work tends to be the most remote-friendly, while roles tied to real-time voice or edge inference are more likely to require on-site presence.
How do you become a nlp engineer?
Start by building a strong foundation in Python, linear algebra, and probability, then work through core NLP concepts like tokenization, language modeling, and sequence labeling. Complete hands-on projects using Hugging Face or spaCy, publish them publicly, and progress toward fine-tuning pre-trained transformer models on real datasets. A degree in computer science or computational linguistics helps, but a portfolio of shipped NLP work carries significant weight with hiring teams.
Can I get hired as a nlp engineer without professional experience?
Yes, entry-level nlp engineer roles exist, and a strong project portfolio can substitute for direct work history. Build end-to-end projects that demonstrate a specific task, such as a named-entity recognition system or a document classifier trained on a public dataset, and document your methodology clearly. Open-source contributions to NLP libraries or published Hugging Face model cards also give hiring managers concrete evidence of your abilities.
What does the nlp engineer interview process look like?
Most companies run three to four rounds starting with a recruiter screen, followed by a technical coding assessment focused on Python and data structures. The core rounds typically include an NLP-specific problem where you design or debug a text processing pipeline, and a system design session covering how you'd architect a production NLP service. Some companies add a research discussion where you walk through a past project or a published paper relevant to their domain.
Where can I find and apply to nlp engineer jobs?
You can find and apply to nlp engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the available roles, find the ones that match your background and target task area, and apply directly to each listing that fits.
See All Nlp Engineer Jobs
Jump back to the full list of openings and apply to any nlp engineer role that fits.
Find Nlp Engineer Jobs