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Machine Learning Engineer Nlp Jobs in California

Parspec

Machine Learning Engineer - 1

San Mateo, CA · On-site

$13/hr

The Opportunity We're looking for a Machine Learning Engineer 1 to join our AI team in San Mateo ... Build and improve NLP pipelines for construction domain tasks like entity extraction ...

RIT Solutions

Machine Learning Engineer

Fremont, CA

Machine Learning Engineer Location: Fremont, CA Duration: 12+ Months Tesla/ $65 About the Role Our direct client is seeking a highly skilled Machine Learning Engineer to join their Software Machine ...

ICW Group

Machine Learning Engineer

San Diego, CA · On-site

PURPOSE OF THE JOB The Machine Learning Engineer (MLE) selected for this role at ICW Group will ... NLP, forecasting, recommender systems, reinforcement learning, deep learning, and optimization.

Icwgroup

Machine Learning Engineer

San Diego, CA · Hybrid

PURPOSE OF THE JOB The Machine Learning Engineer (MLE) selected for this role at ICW Group will ... NLP, forecasting, recommender systems, reinforcement learning, deep learning, and optimization.

ICW Group

Machine Learning Engineer

San Diego, CA · Hybrid

PURPOSE OF THE JOB The Machine Learning Engineer (MLE) selected for this role at ICW Group will ... NLP, forecasting, recommender systems, reinforcement learning, deep learning, and optimization.

Skild AI

Machine Learning Engineer

San Mateo, CA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios ...

eTeam

Senior Machine Learning Engineer

San Jose, CA

$122K - $168K/yr

Technology Lead | Machine Learning | Python Work Location San JoseCA95134 Vendor Rate Contract ... Implement NLP, computer vision, predictive analytics, recommendation systems, or generative AI ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

Avoma Inc

ML Engineer - NLP

Palo Alto, CA

$120K - $140K/yr

Deep Learning / NLP Engineer Join Avoma and work on some of the most challenging NLP problems in ... At least 2+ years of experience with Machine Learning & NLP in a production environment

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

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All JobsMachine Learning Engineer Nlp JobsMachine Learning Engineer Nlp Jobs in California

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.
What are popular job titles related to Machine Learning Engineer Nlp jobs in California? For Machine Learning Engineer Nlp jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Nlp jobs in California look for? The top searched job categories for Machine Learning Engineer Nlp jobs in California are:
Machine Learning Engineer Nlp jobs near you
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.

Machine Learning Engineer

Happy Elements

San Francisco, CA

Full-time

Posted 11 hours ago

Job description

Machine Learning Engineer
Full-time
Responsibilities
  • Build, maintain, and improve efficient and reliable data mining and machine learning models.
  • Design, implement and tune machine learning models, and provide performance feedback.
  • Work closely with data engineers to adapt and improve data pipelines for production models.
  • Work closely with software engineers in putting models into production (interface, SLA, scalability).Qualifications
  • Strong academic background required. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
  • Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow). Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
  • Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
  • Master with SQL or other relational database.
  • Master in building and productionizing end-to-end machine learning systems.
  • Knowledge and experience in cloud computing is a plus.
  • Extensive data modeling and data architecture skills.
  • Advanced math skills (linear algebra, Bayesian statistics, group theory).
  • Ability to consistently exercise independent discretion and judgment on significant matters.
  • Strong analytical, problem-solving and communication skills.
  • Ability to work in a team environment

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