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Machine Learning Engineer Jobs in Oceanside, CA (NOW HIRING)

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

  • Medical

  • Retirement

  • PTO

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 ...

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

  • Medical

  • Retirement

  • PTO

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 ...

Last updated: 3 days ago $70.00 hourly Full-time We are seeking an MLOps Engineer to build, deploy, and optimize machine learning infrastructure that supports scalable, secure, and production-ready ...

Senior Machine Learning Engineer, Robotics

San Diego, CA · On-site

$110K - $152K/yr

For this role, we are looking for a strong Software Engineer with robotics and machine learning experience, who will help us to accelerate the transition of low-level Perception tasks from algorithms ...

Principal Machine Learning Engineer

San Diego, CA · On-site +1

$216K - $378K/yr

  • Medical

  • Retirement

Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company ...

Principal Machine Learning Engineer

San Diego, CA · On-site +1

$216K - $378K/yr

  • Medical

  • Retirement

Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company ...

Principal Machine Learning Engineer

San Diego, CA · On-site

$216K - $378K/yr

  • Medical

  • Retirement

Company Description It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company ...

Showing results 41-60

Machine Learning Engineer information

See Oceanside, CA salary details

$32.6K

$133.2K

$200.2K

How much do machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning engineer in Oceanside, CA is $133,216.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,000.00 and $160,400.00 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 are the most commonly searched types of Machine Learning Engineer jobs in Oceanside, CA?

The most popular types of Machine Learning Engineer jobs in Oceanside, CA are:

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

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

Infographic showing various Machine Learning Engineer job openings in Oceanside, CA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 27% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $133,216 per year, or $64 per hour.

Senior Machine Learning Engineer

Seasats

San Diego, CA • On-site

$180K - $250K/yr

Full-time

Medical, Retirement, PTO

Posted 18 days ago


Job description

Role: 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 in highly remote and often communications-limited environments. To complete persistent missions at scale, the vehicles must be able to perceive and reason about the world around them without humans in the loop. Seasats has built a reliable and increasingly intelligent autonomy stack incorporating onboard sensors and processing, and machine learning is becoming central to how it evolves.

In this role, you'll own the development, training, and edge deployment of the perception models at the heart of that stack. You'll take models from experiment to production: curating fleet data, training and distilling models, optimizing them for embedded hardware, and validating them against real-world maritime conditions. Your work will directly determine how safely and intelligently our vessels navigate dynamic ocean environments.

Role Details:

As a senior member of the team, you'll help set the technical direction for onboard ML at Seasats and raise the bar for how models are built, evaluated, and shipped across the company. You'll work independently on experiments while collaborating closely with the vehicle software team to integrate your work into the larger stack.

On a day-by-day basis, you will:

  • Help define and drive the ML roadmap for vehicle perception
  • Scope and run ML experiments with clearly measurable end states that would positively impact vehicle performance if successful
  • Train, fine-tune, and optimize models sized for compute-limited edge hardware, and validate real-time performance on target hardware
  • Build and maintain the data pipeline: analyzing, organizing, and labeling datasets from our fleet to drive data-driven development
  • Establish evaluation frameworks and metrics that give the team confidence in model behavior before it goes to sea

This is an excellent opportunity to do high impact work, see your models running live on vehicles at sea, and join a fun and hard-working team on the cutting edge of ocean autonomy.

About You:

  • 7+ years in machine learning, including 5+ years solving perception problems in production systems
  • Deep computer vision background, including foundation models and training smaller custom models
  • Track record of shipping performant ML models to edge devices and hands-on experience with model optimization for the edge (quantization, pruning, and inference runtimes such as TensorRT or ONNX Runtime)
  • Strong proficiency in Python, with expert-level fluency in PyTorch and strong working knowledge of OpenCV
  • Experience with MLOps tooling for dataset versioning, experiment tracking, and model deployment
  • Experience working with real-time sensor data (e.g., camera, radar, and IMU streams) and familiarity with classical perception techniques (e.g., filtering, tracking, sensor fusion
  • Demonstrated ability to scope projects independently, lead technical efforts, and mentor other engineers
  • Strong technical communication skills
  • A bias toward getting multiple projects to 80% rather than one project to "perfect", while taking great joy in seeing projects approach perfection over time

In addition, it's nice (though not essential) if you have experience working with:

  • Probabilistic algorithms for obstacle and target tracking, and change detection algorithms for a variety of data types
  • Real-time multi-modal sensor fusion across LiDAR, radar, camera, and IMU data
  • Maritime and/or acoustic data
  • Path-planning and control algorithms

About Seasats:

At Seasats, we're passionate about delivering maritime robotics solutions to redefine the maritime industry. Our primary products are unmanned surface vehicles (USVs), designed to carry sensors at sea for months at a time. Our USVs provide persistent monitoring and data acquisition to defense, scientific, and commercial customers, and have autonomously crossed both the Pacific and Atlantic oceans. After thousands of years in which the only way to gather information from the ocean was to put people on a boat, these uncrewed vessels are transforming how humanity monitors and interacts with the ocean. Here, you'll find the space and opportunity to do your life's best work.

Along with your salary, you'll receive perks including:

  • Stock options
  • Competitive insurance (including a 99% employer-covered Gold HMO plan or other options)
  • 401k matching up to 4% of salary
  • Four free lunches per week
  • An employee activity fund
  • A pet-friendly office
  • Unlimited/Flex PTO

Hiring Notes:

When applying, you'll be asked to provide a resume and answer a few screening questions.

Due to export control requirements applicable to this position, we are only able to consider U.S. persons, as defined by U.S. export control laws. This includes U.S. citizens, lawful permanent residents, and individuals granted asylee or refugee status.

We appreciate diverse perspectives and life experiences, and we're committed to building a team that reflects a wide range of backgrounds. Seasats provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination of any type based on race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, protected veteran status, or any other characteristic protected under federal, state, or local law.

We look forward to reviewing your application!