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Machine Learning Engineer Nlp Jobs in California

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine ... Experience with predictive modeling, natural language processing (NLP), and large language models ...

Machine Learning Engineer LeanData helps the world's fastest-growing companies automate, simplify ... Familiarity with natural language processing (NLP) * Prior experience contributing to the ...

Machine Learning Engineer

San Diego, CA · On-site

$122K - $184K/yr

... g., NLP, multi-media). • 1+ year of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++) • 1+ year of experience using statistics and ...

Experience working with machine learning or LLM model development for various NLP tasks and RAG applications including prompt engineering, training data collection and generation, model fine-tuning ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation ...

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Experience with advanced NLP and Multimodal post-training experience (e.g., model distillation ...

We are looking for developers who are excited about staying at the forefront of deep learning ... You have successfully trained and deployed a deep learning machine model (image, NLP, video, or ...

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Machine Learning Engineer Nlp information

See California salary details

$31.1K

$127.1K

$191K

How much do machine learning engineer nlp jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning engineer nlp in California is $127,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineer NLP roles?

Machine Learning Engineer NLP roles focus on designing, building, and deploying machine learning models that process and understand human language. These engineers work with large datasets to train algorithms for tasks such as text classification, sentiment analysis, language translation, and chatbot development. They combine expertise in computer science, data science, and linguistics, using technologies like deep learning and natural language processing libraries. Their work enables computers to interpret, generate, and respond to human language in meaningful ways.

How does a Machine Learning Engineer specializing in NLP typically collaborate with data scientists and software engineers during a project?

Machine Learning Engineers focused on NLP often work closely with data scientists to translate research findings and experimental models into scalable, production-ready systems. They collaborate with software engineers to integrate NLP models into larger applications, ensuring efficient deployment and performance. Communication and teamwork are key, as engineers must balance model accuracy with system requirements, address technical challenges together, and iterate on solutions based on feedback from cross-functional teams.

What is the difference between Machine Learning Engineer Nlp vs Data Scientist?

AspectMachine Learning Engineer NlpData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops NLP models, deploys ML solutions, collaborates with engineering teamsAnalyzes data, builds models, interprets data insights for business decisions
Employer & Industry UsageTech companies, AI startups, research institutions focusing on NLP applicationsFinance, healthcare, marketing, and tech sectors analyzing large datasets

While both roles require strong data analysis skills and knowledge of machine learning, Machine Learning Engineer Nlp focuses on developing and deploying NLP models, whereas Data Scientists analyze data to generate insights and inform decisions. The roles often overlap but differ in their primary focus and responsibilities.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer specializing in NLP, and why are they important?

To thrive as a Machine Learning Engineer in NLP, you need strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and a background in mathematics or computer science, often supported by a relevant degree. Familiarity with NLP libraries and frameworks such as TensorFlow, PyTorch, spaCy, and Hugging Face Transformers, as well as experience with cloud platforms and version control systems, is crucial. Excellent problem-solving abilities, effective communication, and a collaborative mindset are standout soft skills in this role. These competencies enable the development, deployment, and optimization of NLP models that solve real-world language processing challenges efficiently and innovatively.
Infographic showing various Machine Learning Engineer Nlp job openings in California as of May 2026, with employment types broken down into 2% As Needed, 88% Full Time, 6% Part Time, and 4% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.
NLP Machine Learning Engineer

NLP Machine Learning Engineer

InterSources

San Francisco, CA

Other

Posted 20 days ago


Job description

NLP Machine Learning Engineer

Work on a dataset with millions of customer searches, labeled fashion products, and years of transaction and clickstream data. Work with Client's numerous in-house systems experts for data manipulation, model construction, training, and evaluation. Work on cloud-based infrastructure in your own fully customizable environment. Work in a team with a background in algorithms for deep-learning, information retrieval, and product recommendations. Implement state-of-the-art deep learning models by reviewing and implementing research papers.

Required Skills: M. Sc. Or Ph.D. in math, computer science, statistics, physics, electrical engineering or related field. Experience with NLP in industry or start-up for at least one year. Technologies you should be familiar with: Tensorflow, Keras, Python, Pandas. Concepts you should be familiar with: NLP, NLU, NER, tagging, RNN, Transformers, Attention, Information Retrieval, and Keyword Search. Strong interest in scaling prototypes and turning them into user experiences.


InterSources logo

About InterSources

Sourced by ZipRecruiter

In 2007, Our journey began as pioneers in the realm of technology and security. Since then, InterSources Inc. has evolved into a trusted partner, leading the way in Cloud Security, Cybersecurity, PLG Consulting, Digital Transformation, and Professional Services. With a rich history of excellence and a forward-thinking approach, we continue to secure your digital future and drive innovation. Explore our legacy of success and discover the possibilities that lie ahead.

Company size

51 - 200 Employees

Headquarters location

Fremont, CA, US

Year founded

2007

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