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Executive Full Stack Machine Learning Engineer Jobs

Sr. Machine Learning Engineer, Siri Global

Cupertino, CA · On-site

$151K - $199K/yr

We are particularly interested in "full-stack" machine learning engineers with strong experience in ... and executives. Software engineering experience with both server-based and client-side (e.g. on ...

Senior Machine Learning Engineer

Atlanta, GA · On-site

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Machine Learning Engineer II

Irvine, CA

$104K - $143K/yr

... Learning Engineer at Capital Group, you will create, research, implement, and maintain ... You have experience solving "full stack" machine learning problems, from data collection and ETL ...

Machine Learning Engineer II

Los Angeles, CA · On-site

$105K - $143K/yr

... Learning Engineer at Capital Group, you will create, research, implement, and maintain ... You have experience solving "full stack" machine learning problems, from data collection and ETL ...

Machine Learning Engineer II

Seattle, WA · On-site

$111K - $151K/yr

... Learning Engineer at Capital Group, you will create, research, implement, and maintain ... You have experience solving "full stack" machine learning problems, from data collection and ETL ...

Machine Learning Engineer II

Seattle, WA · On-site

$111K - $151K/yr

... Learning Engineer at Capital Group, you will create, research, implement, and maintain ... You have experience solving "full stack" machine learning problems, from data collection and ETL ...

As a Machine Learning Engineer, you will shape the technical direction of the company by automating ... Required : • 3 to 5 years of industry experience in full-stack Deep Learning and Computer Vision ...

Machine Learning Engineer

Mount Pleasant, SC · On-site

$109K - $131K/yr

We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics ...

Machine Learning Engineer Location: Long Island City, NY 11101 (Onsite 4 Days/week) Type: Permanent ... Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless ...

Machine Learning Engineer Primary Location : Pleasanton, California V-Soft Consulting is currently ... technology stacks. As a valued V-Soft Consultant, you're eligible for full benefits (Medical ...

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Executive Full Stack Machine Learning Engineer information

See salary details

$44.5K

$134.8K

$190.5K

How much do executive full stack machine learning engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for executive full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

Will AI replace full-stack dev?

As an Executive Full Stack Machine Learning Engineer, it is unlikely that AI will fully replace full-stack developers, as their roles require complex problem-solving, creativity, and understanding of business needs that AI cannot replicate. AI tools can automate certain coding tasks and improve efficiency, but human oversight and expertise remain essential for designing, integrating, and maintaining full-stack applications. The evolving landscape emphasizes collaboration between AI and developers rather than replacement.

What engineer makes $500,000 a year?

An executive full stack machine learning engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in AI and software development, and working at large tech companies or startups with competitive compensation packages. High salaries often include base pay, bonuses, and stock options, reflecting seniority and expertise in the field.

Will MLE be replaced by AI?

An Executive Full Stack Machine Learning Engineer designs and implements AI systems, but AI is a tool that complements rather than replaces such roles. While automation and AI advancements can handle certain tasks, skilled engineers are needed for developing, maintaining, and improving complex machine learning solutions. Continuous learning and expertise in programming, data analysis, and model deployment remain essential in this field.

What is the salary of full-stack machine learning engineer?

The salary of a full-stack machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those requiring specialized skills in deep learning or cloud platforms may offer higher compensation.

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

More about Executive Full Stack Machine Learning Engineer jobs
What cities are hiring for Executive Full Stack Machine Learning Engineer jobs? Cities with the most Executive Full Stack Machine Learning Engineer job openings:
What are the most commonly searched types of Full Stack Machine Learning Engineer jobs? The most popular types of Full Stack Machine Learning Engineer jobs are:
What states have the most Executive Full Stack Machine Learning Engineer jobs? States with the most job openings for Executive Full Stack Machine Learning Engineer jobs include:
Infographic showing various Executive Full Stack Machine Learning Engineer job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $134,771 per year, or $64.8 per hour.

Sr. Machine Learning Engineer, Siri Global

Apple

Cupertino, CA • On-site

$151K - $199K/yr

Full-time

Re-posted 29 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 676 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Join the Siri team at Apple! Build and contribute to a product and company that that is building products, personal devices, and software designed to enrich people's lives. Work on building and advancing the world's most popular intelligent assistant that helps millions of people get things done - just by asking.
Global Siri works to take Siri to the next level of intelligence and capabilities in all languages and markets. We build machine learning models, systems, and software that understands the intents hundreds of millions of users and their billions of requests to Siri, on Apple devices such as iPhone, iPad, Apple Watch, Mac, AirPods, HomePod, Vision Pro and Apple TV. On the Global Scaling, Data, and Tools team, we work on ML modeling and algorithms, data platforms and technologies, and end-to-end ML product engineering to surprise and delight customers around the world in the languages that they speak.
Description
We seek a Senior Machine Learning Engineer / Tech Lead who is passionate about collaborating across teams in Siri and Apple to design, build, and deploy world-class machine learning systems that help Siri best serve the needs of our users. In this role, you will work on creating and improving the accuracy, speed, reliability, and capability of Global Siri's models and systems. We are particularly interested in "full-stack" machine learning engineers with strong experience in research, software engineering, and have strong leadership potential.
You should be passionate about building outstanding products, and using the full spectrum of your skills to drive technical and organizational advancements. The ideal candidate is equally comfortable with the latest academic/research advancements in ML, LLMs, NLP, and related areas, diving into all parts of the full engineering/machine learning stack to diagnose user-facing issues and develop principled solutions, and deeply engaging in product metrics and goals with product managers, designers, and executives. Software engineering experience with both server-based and client-side (e.g. on-device) models is a definite asset. In this role, the ability to communicate complex technical ideas to diverse audiences, including research scientists, data scientists, engineers, designers, managers, and other stakeholders across Siri and Apple is also essential.
This position involves a wide variety of skills and innovation. In addition to your individual technical contributions, there are immense opportunities to multiply the impact those around you by mentoring, motivating and challenging engineers to deliver features at high quality. If you are looking for a role that is challenging, impactful, has immense growth opportunities, this role is for you.
Minimum Qualifications
Master's or PhD degree in computer science, software engineering, machine learning, language technologies, or related fields; outstanding candidates with Bachelor's degrees and multiple years years of significant engineering/product experience will also be considered
10+ years of experience developing, shipping, and measuring industry-scale machine learning-based software systems; experience working on large-scale NLU systems a strong asset.
Experience as a senior engineer, tech lead, or engineering manager for a machine learning-based product, including mentoring other engineers, working with program and product managers, and communicating accomplishments, metrics, and challenges to cross-functional stakeholders and leaders
Expertise and experience in Large Language Models (LLMs) or other foundation models, ideally demonstrated through publications or shipping foundation model-based features and products.
Strong background in machine learning, deep learning, and foundation models, as demonstrated through top-tier publications and/or successful development of training data, models, or software in commercial machine learning systems.
Excellent software engineering skills: Proficiency in at least one object-oriented language (e.g. Java, C++, Objective-C, or Swift), scripting languages (e.g. Python, Ruby, bash), and deep learning/machine learning frameworks (e.g. TensorFlow, PyTorch, or CoreML)
Outstanding problem solving, critical thinking, creativity, organizational, design, and interpersonal skills; ability to work with all levels of engineers, scientists, designers, and communicate effectively with management, leadership, and cross-functional partners
Preferred Qualifications
Experience in data science and analytics, including data annotation, statistical analyses, A/B testing, and/or conducting experiments and investigations in large-scale usage data environments
Self-starter with a proven ability to handle multiple projects with strict deadlines
Experience in the iOS development ecosystem (e.g. Swift, Objective-C, CoreML, or SiriKit) is a plus
Experience in localization, internationalization, machine translation, or language technologies is an asset

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

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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