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

General Atomics

Machine Learning Engineer

Poway, CA · On-site

We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

The Marlin Alliance, Inc. is seeking a talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

The Marlin Alliance, Inc. is seekinga talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced ...

Apple Inc.

Video Machine Learning Engineer

San Diego, CA · On-site

$139.50 - $258.10/hr

We are seeking a passionate and innovative machine learning engineer to join a team that is shaping the future of video intelligence. Our team develops cutting‑edge machine learning technologies ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in El Cajon, CA

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 3, 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.

More about Machine Learning Engineer jobs

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:

Machine Learning Engineer jobs near you
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

General Atomics

Poway, CA • On-site

Full-time

Re-posted 20 days ago

Key responsibilities

  • Develops and communicates insights and algorithms related to machine learning and statistical modeling.

  • Uses programming languages and technologies to translate algorithms and technical specifications into code, perform testing, debugging, and complete documentation.

  • Interfaces with external vendors and partners to integrate their technology into the team's autonomy stack.

General Atomics rating

9.0

Company rating: 9.0 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

10th of 72 rated aerospace companies

Job description

Job Summary
General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.
We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous systems that enable unmanned aerial systems (UAS) to execute autonomous missions.
DUTIES AND RESPONSIBILITIES:
  • Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope.
  • In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy.
  • In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code.
  • Completes programming and implements efficiencies, performs testing and debugging.
  • Completes documentation and procedures for installation and maintenance.
  • Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope.
  • Lead technical teams and scope challenging projects into executable sprints.
  • Drive code reviews to help team adhere to general DevSecOps and MLOps best practices.
  • Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution.
  • Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.
  • Interface with external vendors and partners to integrate their technology into the team's autonomy stack.
  • Maintains the strict confidentiality of sensitive information.
  • Performs other duties as assigned.
  • Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company. Expected to work in a safe manner in accordance with established operating procedures and practices.
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
Job Qualifications
  • Typically requires a bachelors or master's degree in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and two or more years of machine learning experience with a bachelors degree. May substitute equivalent machine learning engineer experience in lieu of education.
  • Must have an understanding of machine learning concepts, principles, and theory.
  • Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance.
  • Experience in developing and leading scalable software architectures from scratch.
  • Experience in optimizing AI models to meet edge processing requirements.
  • Strong coding skills in Java, Java Script, C/C++, Python
  • Experience in AI frameworks such as Tensorflow and pyTorch.
  • Excellent verbal and written communication skills.
  • Must be able to architect, design, and develop complex software.
  • Technical expertise in the application of engineering principles, concepts, theory, and practice as well as project management and leadership skills including organizing, planning, scheduling, and coordinating workloads to meet established deadlines or milestones.
  • Active membership and participation in relevant conference and professional society organizations.
  • Demonstrated recent history of academic quality publications in the area of AI/ML and autonomy.
  • Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment.
  • Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience.
  • Must be able to work both independently and on a team.
  • Able to work extended hours as required.
  • Customer focused, must be able to work on a self-initiated basis and in a team environment, and able to work extended hours and travel as required.
  • Ability to obtain and maintain a DoD security clearance is required.

What General Atomics employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About General Atomics

Sourced by ZipRecruiter

General Atomics (GA), and its affiliated companies, is one of the world's leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.

Industry

Space research administration

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1955

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