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Machine Learning Natural Language Processing Jobs

Westlake Village, CA (Onsite, NO REMOTE) Excellent contract-to-hire job opportunity As a Software Developer for the Artificial Intelligence team, work on Machine Learning, Natural Language Processing ...

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Machine Learning Natural Language Processing information

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How much do machine learning natural language processing jobs pay per hour?

As of Jun 24, 2026, the average hourly pay for machine learning natural language processing in the United States is $19.89, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $21.63 per hour, depending on experience, location, and employer.

How do professionals in Machine Learning Natural Language Processing typically collaborate with cross-functional teams?

In Machine Learning Natural Language Processing (NLP) roles, collaboration with cross-functional teams is essential. NLP professionals frequently work alongside data engineers to gather and preprocess large datasets, software developers to integrate models into products, and product managers to align technical solutions with business goals. Regular communication, agile methodologies, and collaborative problem-solving sessions are common to ensure that NLP models are both technically sound and user-oriented. This teamwork not only enhances the effectiveness of NLP solutions but also provides opportunities to learn from colleagues with diverse expertise.

What engineers make $500,000?

Senior machine learning engineers and natural language processing (NLP) specialists with extensive experience, advanced skills in deep learning frameworks, and strong industry demand can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on product development.

What is a Machine Learning Natural Language Processing (NLP) specialist?

A Machine Learning Natural Language Processing (NLP) specialist is a professional who designs, develops, and implements algorithms and models that allow computers to understand, interpret, and generate human language. They use machine learning techniques to work on tasks such as text classification, sentiment analysis, language translation, and speech recognition. NLP specialists often work with large datasets and require strong skills in programming, linguistics, and data science. Their work enables applications like chatbots, virtual assistants, and search engines to better process human language.

Which 3 jobs will survive AI?

For a Machine Learning Natural Language Processing professional, roles such as AI ethics specialists, data scientists, and machine learning engineers are expected to persist due to their focus on developing, managing, and overseeing AI systems. These jobs require advanced technical skills, domain expertise, and ongoing adaptation to new tools and algorithms, making them more resilient to automation.

What are the key skills and qualifications needed to thrive as a Machine Learning Natural Language Processing specialist, and why are they important?

A Machine Learning Natural Language Processing (NLP) specialist needs strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and advanced knowledge in linguistics or computational linguistics, often supported by a relevant degree. Familiarity with NLP libraries (like NLTK, spaCy, or Hugging Face Transformers), experience with machine learning frameworks (such as TensorFlow or PyTorch), and sometimes certifications in data science or AI are typically required. Excellent problem-solving ability, collaboration, and effective communication are crucial soft skills to excel in this field. These skills enable the development of robust NLP models, smooth integration into real-world applications, and effective teamwork on complex projects.

What is the role of machine learning in natural language processing?

In natural language processing (NLP), machine learning enables systems to automatically analyze, understand, and generate human language by training models on large datasets. Machine learning algorithms, such as neural networks and classifiers, are used to perform tasks like language translation, sentiment analysis, and speech recognition, making NLP applications more accurate and efficient. For a machine learning NLP role, knowledge of programming, data preprocessing, and relevant tools like Python and TensorFlow is essential.

What is the salary of NLP machine learning?

The salary for machine learning professionals specializing in natural language processing (NLP) typically ranges from $80,000 to $150,000 annually, depending on experience, location, and education. Entry-level roles may start lower, while experienced specialists or those with advanced skills in deep learning and NLP tools can earn higher salaries.
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What cities are hiring for Machine Learning Natural Language Processing jobs? Cities with the most Machine Learning Natural Language Processing job openings:
What states have the most Machine Learning Natural Language Processing jobs? States with the most job openings for Machine Learning Natural Language Processing jobs include:
What job categories do people searching Machine Learning Natural Language Processing jobs look for? The top searched job categories for Machine Learning Natural Language Processing jobs are:
Infographic showing various Machine Learning Natural Language Processing job openings in the United States as of June 2026, with employment types broken down into 32% Full Time, 65% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $41,370 per year, or $19.9 per hour.
Machine Learning Engineer, Web Indexing Team

Machine Learning Engineer, Web Indexing Team

Apple

Santa Clara, CA

$171K - $302K/yr

Full-time

Medical, Dental, Retirement

Posted 8 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 662 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish.
Do you want to make Siri and Apple products smarter for our users? The MLPT & Infrastructure teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages, and Lookup.
As part of this group, you will work within one of the most exciting high-performance computing environments, with petabytes of data and millions of queries per second, and have the opportunity to imagine and build products that delight our customers every single day.
Description
We design and build infrastructures to support features that empower billions of Apple users through advanced intelligence systems. Our team processes trillions of links to find the best content to surface to users via search and other intelligent features. We also analyze pages to extract critical features for indexing, ranking, and retrieval. We apply statistical analysis to enhance link selection, content freshness, retrieval rates, and extraction quality, among many other aspects. Furthermore, we are building a generic Retrieval-Augmented Generation (RAG) indexing infrastructure framework to allow indexing building customization and support fast experiment iteration. You’ll have the opportunity to dive deeper into RAG systems, as well as large-scale data processing, managing trillions of records, petabytes of data, and the incredible complexity behind Apple Intelligence’s products.","responsibilities":"Design, build, and scale infrastructure systems that support intelligent features powering billions of Apple users
Process and analyze trillions of links to surface the highest quality content across search and other intelligent features
Develop pipelines to extract critical features for indexing, ranking, and retrieval at massive scale
Apply statistical analysis to improve link selection, content freshness, retrieval rates, and extraction quality
Architect and contribute to a generic Retrieval-Augmented Generation (RAG) indexing infrastructure framework, enabling indexing customization and fast experimentation
Partner cross-functionally with machine learning, NLP, and product teams to deliver impactful, high-quality solutions
Mentor and provide technical guidance to junior engineers on the team
Preferred Qualifications
10+ years of software engineering experience, with demonstrated impact at a senior or staff level
Experience designing and building RAG systems or other AI/ML indexing pipelines
Background in machine learning, natural language processing, or information retrieval
Experience managing systems operating at petabyte scale with trillions of records
Strong communication skills with a track record of influencing technical direction across teams
MS or PhD in Computer Science or a related field, or equivalent practical experience
Minimum Qualifications
7+ years of software engineering experience, with a strong focus on large-scale distributed systems or infrastructure
Strong coding proficiency in one or more languages (e.g., Python, Java, Go, C++)
Solid foundation in computer science fundamentals including algorithms and data structures
Hands-on experience with large-scale data processing and MapReduce-style frameworks (e.g., Spark, Hadoop)
Experience with cloud services, particularly AWS (S3, EC2, EKS) and/or Kubernetes-based orchestration
Proven ability to operate independently and drive projects end-to-end in a collaborative team environment
MS or PhD in Computer Science or a related field, or equivalent practical experience
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 $171,600 and $302,200, 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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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976