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.
Find Nlp Engineer JobsOverview
Showing 5 of 10+ Nlp Engineer jobs
Artificial Intelligence/Machine Learning Engineer 1 - (NLP, AWS, PyTorch)
Clearance: TS/SCI - Polygraph required within 7 years
Position ID: 25-8967-AIML1
Location: Annapolis Junction, Maryland
Description:
Designs, creates, tests, and productizes AI/ML algorithms to solve business challenges and support customer requirements.
Works across model architecture, data pipeline interaction, and metrics application, interpretation, and presentation; requires familiarity with application development, infrastructure management, data engineering, and data governance.
Uses training, retraining, deploying, scheduling, monitoring, and iterative improvement to create scalable solutions, and may lead geographically diverse teams as a primary POC for AI-related matters.
- Build, train, and fine-tune machine learning models, particularly language models
- Apply best practices in model training, tuning, and optimization
- Design and implement solutions for model performance improvement
- Conduct rigorous model evaluation, including performance analysis and benchmarking
- Perform error analysis, debugging, and model diagnostics to ensure quality and reliability
- Work with cloud-based AI platforms, especially AWS Sagemaker, to deploy and scale models
- Integrate machine learning models into production environments, ensuring seamless integration with other systems
- Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end)
- Collaborate with software engineers to build scalable and efficient deployment pipelines
- Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions
- Document workflows, model design processes, and technical specifications
- Select appropriate data sets
- Perform statistical analysis
- Run machine learning algorithms
- Use results to improve models
- Train and retrain systems when needed
- Run standard test and evaluation protocols
- Provide system integration oversight
Position Required Skills:
- Knowledge and experience of language models, including Marian and multi-lingual model development
- Knowledge of computational linguistics
- Experience with open-source model libraries
- Deep Learning Containers (DLC) and GPU technologies
- Optimization and tuning
- Strong Java, C, and C++ programming experience
- Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face
- Hands-on experience with AWS tools like SageMaker, Lambda, EC2, and S3
- Experience in developing full-stack software applications (JavaScript, Python, Java, etc.)
- Solid understanding of data structures, algorithms, and system design
- Extensive experience in machine learning model development, including natural language processing (NLP)
- Experience with model evaluation, optimization, and performance monitoring
- Experience with model versioning and management using tools such as MLFlow or Git
- Familiarity with containerization tools such as Kubernetes
Position Desired Skills:
- Willingness to support occasional on-call duties
- Experience in a government or defense-related environment
- Experience with secure data handling and compliance requirements
- Experience working with Large Language Models (LLMs)
AIML1 Qualifications:
Two (2) years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
A B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
Three (3) years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.
Salary Range: $170k-$208k (Annually)
The range displayed above is a likely salary range for this position. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possible contractual requirements and could fall outside of this range.
Akina is a Woman Owned, Service Disabled, Veteran Owned, Small Business, looking for talented and ambitious individuals to join our team. We offer a generous compensation package that includes 24 days PTO accrued annually and 11 federal holidays. Our 401k is 100% vested on your start date and the company makes a direct contribution worth 10% of your salary. Akina covers 100% of healthcare costs for employees and 50% toward dependents. We offer educational assistance towards college classes and will cover costs associated with job related training and certifications.
Akina is committed to excellence and creating innovative and flexible solutions for our clients. We are a small company with an open ear to our employees' needs in order to attract and retain quality talent that enables our customer's mission.
We are an equal employment opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
www.akina-inc.com/careers
Artificial Intelligence/Machine Learning Engineer 1 - (NLP, AWS, PyTorch)
Clearance: TS/SCI - Polygraph required within 7 years
Position ID: 25-8967-AIML1
Location: Annapolis Junction, Maryland
Description:
Designs, creates, tests, and productizes AI/ML algorithms to solve business challenges and support customer requirements.
Works across model architecture, data pipeline interaction, and metrics application, interpretation, and presentation; requires familiarity with application development, infrastructure management, data engineering, and data governance.
Uses training, retraining, deploying, scheduling, monitoring, and iterative improvement to create scalable solutions, and may lead geographically diverse teams as a primary POC for AI-related matters.
- Build, train, and fine-tune machine learning models, particularly language models
- Apply best practices in model training, tuning, and optimization
- Design and implement solutions for model performance improvement
- Conduct rigorous model evaluation, including performance analysis and benchmarking
- Perform error analysis, debugging, and model diagnostics to ensure quality and reliability
- Work with cloud-based AI platforms, especially AWS Sagemaker, to deploy and scale models
- Integrate machine learning models into production environments, ensuring seamless integration with other systems
- Contribute to the development and maintenance of the full stack for AI model-based applications (front-end and back-end)
- Collaborate with software engineers to build scalable and efficient deployment pipelines
- Work closely with data scientists, product teams, and engineers to translate business requirements into technical solutions
- Document workflows, model design processes, and technical specifications
- Select appropriate data sets
- Perform statistical analysis
- Run machine learning algorithms
- Use results to improve models
- Train and retrain systems when needed
- Run standard test and evaluation protocols
- Provide system integration oversight
Position Required Skills:
- Knowledge and experience of language models, including Marian and multi-lingual model development
- Knowledge of computational linguistics
- Experience with open-source model libraries
- Deep Learning Containers (DLC) and GPU technologies
- Optimization and tuning
- Strong Java, C, and C++ programming experience
- Strong proficiency in AI/ML frameworks such as TensorFlow, PyTorch, or Hugging Face
- Hands-on experience with AWS tools like SageMaker, Lambda, EC2, and S3
- Experience in developing full-stack software applications (JavaScript, Python, Java, etc.)
- Solid understanding of data structures, algorithms, and system design
- Extensive experience in machine learning model development, including natural language processing (NLP)
- Experience with model evaluation, optimization, and performance monitoring
- Experience with model versioning and management using tools such as MLFlow or Git
- Familiarity with containerization tools such as Kubernetes
Position Desired Skills:
- Willingness to support occasional on-call duties
- Experience in a government or defense-related environment
- Experience with secure data handling and compliance requirements
- Experience working with Large Language Models (LLMs)
AIML1 Qualifications:
Two (2) years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
A B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
Three (3) years of additional machine learning experience on projects with similar machine learning processes may be substituted for a bachelor’s degree.
Salary Range: $170k-$208k (Annually)
The range displayed above is a likely salary range for this position. This is not, however, a guarantee of compensation or salary. Rather, salary will be set based on experience, geographic location and possible contractual requirements and could fall outside of this range.
Akina is a Woman Owned, Service Disabled, Veteran Owned, Small Business, looking for talented and ambitious individuals to join our team. We offer a generous compensation package that includes 24 days PTO accrued annually and 11 federal holidays. Our 401k is 100% vested on your start date and the company makes a direct contribution worth 10% of your salary. Akina covers 100% of healthcare costs for employees and 50% toward dependents. We offer educational assistance towards college classes and will cover costs associated with job related training and certifications.
Akina is committed to excellence and creating innovative and flexible solutions for our clients. We are a small company with an open ear to our employees' needs in order to attract and retain quality talent that enables our customer's mission.
We are an equal employment opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.
www.akina-inc.com/careers
Nlp Engineer Jobs by Experience Level
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Find Nlp Engineer JobsNlp Engineer Job Market
Who's Hiring
Top Industries Hiring
- Technology & Software
- Investment & Asset Management
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 TikTok, FIS, and BV Teck, with the largest share of openings in California, Virginia, and Florida, based on current listings on Migrate Mate as of November 2026. Demand is particularly concentrated at companies building conversational AI, enterprise search, and healthcare documentation tools.
How many nlp engineer jobs are remote?
About 75% of nlp engineer openings are fully remote or hybrid as of November 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 10 Nlp Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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