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Machine Learning Engineer Jobs in El Cajon, CA (NOW HIRING)

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250,000 / yr + stock options, 401k matching, and other benefits Role Overview: Seasats' vehicles operate ...

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on -- training, fine-tuning, inference, RAG ...

Sr. Machine Learning Engineer

San Diego, CA · On-site

$111K - $152K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Sr. Machine Learning Engineer

San Diego, CA

$111K - $152K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

Showing results 41-60

Machine Learning Engineer information

See El Cajon, CA salary details

$32.9K

$134.4K

$202K

How much do machine learning engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for machine learning engineer in El Cajon, CA is $134,435.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $161,800.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Machine Learning Engineer jobs in El Cajon, CA look for?

The top searched job categories for Machine Learning Engineer jobs in El Cajon, CA are:

What cities near El Cajon, CA are hiring for Machine Learning Engineer jobs?

Cities near El Cajon, CA with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in El Cajon, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $134,435 per year, or $64.6 per hour.

Machine Learning Engineer Platform - iCloud Mail Intelligence

Apple

San Diego, CA

$175K - $263K/yr

Full-time

Medical, Dental, Retirement

Re-posted 17 days ago


Key responsibilities

  • Design, develop, and deploy end-to-end machine learning applications and models that improve the iCloud experience

  • Build high-performance, scalable, and extensible services for delivering ML models and features into production

  • Partner with multi-functional engineering teams to enhance existing systems and implement new ML-driven experiences across Mail, Calendar, and Contacts


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 681 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Are you passionate about applying your deep understanding of machine learning technologies
and data platform skills in creative ways? Apple's iCloud Mail Intelligence Platform team is
looking for an excellent Machine Learning Engineer that can continuously innovate on the
iCloud experience across Mail, Calendar, and Contacts.
The team is responsible for building groundbreaking ML infrastructure that supports intelligent experiences for hundreds of millions
of users worldwide.
Description
Consider joining a team that brings intelligent experiences to Mail, Calendar, and Contacts for
millions of iCloud customers. Quality and user privacy are central to everything we build.
We are looking for an experienced ML engineer who has a strong background in building high-
performance, scalable, and extensible systems using big data, machine learning, and artificial
intelligence technologies. You recognize the importance of writing functional specifications and
collaborating on high-level design documents. You craft efficient, well-documented code with
comprehensive unit and end-to-end tests.
The successful candidate will demonstrate an ability to collaborate with multi-functional
engineering teams to expand ML infrastructure capabilities and build ML-driven experiences
across Mail, Calendar, and Contacts. You will leverage existing AI/ML infrastructure and
contribute to building new platform services that accelerate machine learning development.
You will also design, build, and deploy ML models and features that improve the iCloud
experience for millions of users.","responsibilities":"Standardize and accelerate ML feature development across Mail, Calendar, and Contacts
Design, develop, and deploy end-to-end machine learning applications and models that improve the iCloud experience
Work with large volumes of data; extract and manipulate large datasets using tools such as Spark, SQL, command line, and scripting languages
Build high-performance, scalable, and extensible services for delivering ML models and features into production
Establish and apply standards for evaluation, testing, and model observability
Collect ongoing qualitative and quantitative feedback from the user population and iterate based on the findings
Partner with multi-functional engineering teams to enhance existing systems and implement new ML-driven experiences across Mail, Calendar, and Contacts
Preferred Qualifications
5+ years of ML engineering experience (or equivalent depth) with a track record of technical leadership on large-scale ML systems or ML platforms that standardize workflows across multiple teams
Experience with agent-based architectures, orchestration frameworks, and LLM observability and evaluation tooling
Expertise with LLMs, including fine-tuning, prompt engineering, embeddings, retrieval systems, evaluation, and integration into production systems
Experience deploying models across multiple runtimes (e.g., on-device, server-side)
Understanding of privacy-preserving ML techniques and responsible data handling
Familiarity with email, calendar, or contacts domains, or other communications and productivity systems
MS/PhD in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience
Minimum Qualifications
Strong production experience training, evaluating, and operating ML models with end-to-end ML pipelines: data processing, feature engineering, training, serving, and monitoring
Experience with large-scale distributed systems including data processing, event-driven architectures and both real-time and batch inference
Strong programming skills in one or more production languages (e.g., Python, Java, Scala, Kotlin, Go)
Demonstrated ability to drive projects independently from problem definition to production
Deep understanding of predictive modeling and machine learning algorithms across supervised and unsupervised learning
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 $175,000 and $263,300, 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.

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Apple logo

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