1

Embedded Machine Learning Engineer Jobs in Vista, CA

Senior Machine Learning Engineer

Vista, CA · On-site

$107K - $195K/yr

We are seeking a Senior Machine Learning Engineer to work on MLOPS that support the testing, and release of object detection algorithms for our portfolio of products that help safeguard the flow of ...

We are seeking a Senior Machine Learning Engineer to work on MLOPS that support the testing, and release of object detection algorithms for our portfolio of products that help safeguard the flow of ...

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 ...

New

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... embedded hardware, and validating them against real-world maritime conditions. Your work will ...

Machine Learning Engineer- GenAI

San Diego, CA · On-site

$150.40 - $277.60/hr

The Product Operations team is looking for an extraordinary engineer to join our team. You will help design and implement our machine learning strategy to the substantial supply chain and help build ...

Lead Machine Learning Engineer

Carlsbad, CA · On-site

$187.90 - $252/hr

Lead Machine Learning Engineer Req ID: 10154653 Disney Entertainment and ESPN Product & Technology Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN ...

New

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... embedded hardware, and validating them against real-world maritime conditions. Your work will ...

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... embedded hardware, and validating them against real-world maritime conditions. Your work will ...

Senior Machine Learning Engineer

Vista, CA · On-site

$107K - $195K/yr

We are seeking a Senior Machine Learning Engineer to work on MLOPS that support the testing, and release of object detection algorithms for our portfolio of products that help safeguard the flow of ...

Showing results 21-40

Embedded Machine Learning Engineer information

See Vista, CA salary details

$71.6K

$156.8K

$177.9K

How much do embedded machine learning engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for embedded machine learning engineer in Vista, CA is $156,789.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,400.00 and $176,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an embedded machine learning engineer?

To thrive as an Embedded Machine Learning Engineer, you need expertise in machine learning algorithms, embedded systems programming (C/C++ or Python), and a solid understanding of hardware constraints, usually supported by a degree in computer science, electrical engineering, or related fields. Familiarity with tools like TensorFlow Lite, ONNX, microcontroller SDKs, and experience with real-time operating systems (RTOS) are typically required. Strong problem-solving, communication skills, and the ability to collaborate across multidisciplinary teams help you stand out in this role. These skills are crucial for efficiently deploying intelligent models on resource-constrained devices, ensuring optimal performance and seamless integration in real-world applications.

What does an embedded machine learning engineer do?

An Embedded Machine Learning Engineer designs and implements machine learning models that can run efficiently on embedded systems, such as microcontrollers and edge devices. Their work involves optimizing algorithms to fit within the resource constraints of these devices, integrating ML models into hardware, and ensuring real-time performance. They collaborate closely with hardware engineers and software developers to deploy intelligent features in products like smart sensors, IoT devices, and autonomous systems.

What are some common challenges faced by embedded machine learning engineers when deploying models to hardware devices?

One of the main challenges for Embedded Machine Learning Engineers is optimizing machine learning models to run efficiently on devices with limited memory, processing power, and energy capacity. Ensuring real-time performance while maintaining accuracy often requires model quantization, pruning, or using lightweight architectures. Additionally, engineers must carefully manage hardware-software integration and address issues like compatibility with various microcontrollers and ensuring secure, reliable updates for deployed models. Close collaboration with hardware engineers and software developers is essential to overcome these challenges and deliver robust embedded AI solutions.

What is the difference between Embedded Machine Learning Engineer vs Firmware Engineer?

AspectEmbedded Machine Learning EngineerFirmware Engineer
Required CredentialsBachelor's/Master's in Computer Science, Electrical Engineering, or related; knowledge of ML frameworksBachelor's in Electrical Engineering, Computer Engineering, or related; embedded systems experience
Work EnvironmentDevelops ML models for embedded devices, often in IoT or smart devicesDesigns and implements low-level firmware for hardware devices
Industry UsageTech companies, IoT, consumer electronics, automotiveConsumer electronics, automotive, industrial equipment

The Embedded Machine Learning Engineer focuses on integrating machine learning models into embedded systems, while the Firmware Engineer specializes in developing low-level software for hardware devices. Both roles require embedded systems knowledge but differ in their core focus and skill sets.

What cities near Vista, CA are hiring for Embedded Machine Learning Engineer jobs? Cities near Vista, CA with the most Embedded Machine Learning Engineer job openings:
Infographic showing various Embedded Machine Learning Engineer job openings in Vista, CA as of July 2026, with employment types broken down into 1% As Needed, 70% Full Time, 26% Part Time, 1% Temporary, and 2% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $156,789 per year, or $75.4 per hour.

Senior Machine Learning Engineer

The Marlin Alliance

San Diego, CA

$130K - $171K/yr

Full-time

Re-posted 16 days ago


Job description

The Marlin Alliance, Inc. is seeking a Senior Machine Learning Engineer to design, develop, and implement advanced machine learning models and algorithms in support of naval applications. This role requires deep technical expertise in modern machine learning methods, distributed systems, cloud-native development, and software engineering best practices. The Senior ML Engineer will collaborate with multidisciplinary teams to deliver mission-focused AI solutions that integrate into operational Navy environments.

Incorporated in 2002, The Marlin Alliance is a digital transformation company dedicated to ensuring our clients compete and win in tomorrows digital world. We specialize in creating technical solutions that allow for seamless execution of automated business processes and the generation of governed, machine-consumable data. From strategic planning to advanced analytics and cybersecurity, our team provides cutting-edge, cross-disciplinary solutions. We are seeking motivated professionals who share our agile, solution-oriented mindset and are ready to deliver the real, practical results relied upon by our clients.

Citizenship and Clearance requirements:

  • U.S. Citizenship required
  • No dual citizenship
  • Active TS security clearance required
  • Active TS SCI security clearance preferred

Location - ON-Site near one of the following locations:

  1. 1st Space Brigade - Fort Carson, CO
  2. Air Force TENCAP - Colorado Springs, CO
  3. NIWC LANT - Charleston, SC
  4. Buckley Space Force Base - Denver, CO
  5. NAVWAR - San Diego, CA

Travel:

  • 15%

Responsibilities:

  • Collaborate with cross-functional teams to understand and address Navy operational challenges using data pipelines and analytics.
  • Design, develop, and implement data pipelines and analytics for naval applications.
  • Perform exploratory data analysis, algorithm development, and testing.
  • Normalize and structure data to common standards for interoperability.
  • Work with multiple data formats, including CSV, JSON, XML, Parquet, and ORC.
  • Develop and deploy data pipelines and analytics in real-world operational environments.
  • Deploy, monitor, and optimize data pipelines to ensure high performance and reliability.
  • Implement event streaming pipelines using Apache Kafka, AWS Kinesis, RabbitMQ, or ZeroMQ.
  • Utilize distributed computing platforms such as AWS Lambda, Dask, or Spark.
  • Leverage cloud-native tools including AWS S3, RDS, EFS, SNS, and SQS.
  • Utilize data pipeline frameworks such as AirByte, Apache Airflow, dbt, Apache Iceberg, and Snowflake.
  • Work with GIS data using ArcGIS, PostGIS, and related tooling.
  • Implement containerized environments using Docker or Kubernetes.
  • Apply cybersecurity principles in the context of secure DoD data applications.
  • Communicate findings and engineering solutions effectively with technical and mission stakeholders.

Required Skills and Experience:

  • Experience as a data scientist, data engineer, geospatial engineer, machine learning engineer, or software engineer.
  • Proven experience developing and deploying algorithms, mathematical models, or machine learning models in real-world applications.
  • Strong programming skills in Python.
  • Familiarity with cloud platforms (e.g., AWS, Azure) or containerization technologies (e.g., Docker, Kubernetes).
  • Familiarity with software engineering best practices, including Git.
  • Strong programming skills in Java, C++, Go, or Rust.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to work effectively in a collaborative team environment.
  • Ability to safely carry tools, equipment, and materials aboard ship, including ascending and descending shipboard ladders(stairwells) and navigating confined spaces while maintaining required points of contact. Tools and equipment will weigh no more than 50 lbs.
  • Ability to perform required work aboard Navy vessels and in shipboard environments, including navigating narrow passageways, ascending and descending ladders (stairwells), working on elevated platforms, and operating in variable sea conditions.
  • Ability to perform activities on a recurring basis during shipboard operations or testing evolutions.
  • Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).
  • Candidates should be prepared to complete a coding exercise as part of the interview process.

Preferred Skills and Experience:

  • Experience with distributed computing and parallel processing.
  • Experience with CI/CD pipelines and automation tools (GitHub Actions, GitLab CI, Jenkins).
  • Experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience with cloud-native architecture and software API design.
  • Experience integrating machine learning into operational DoD systems or edge computing environments.
  • Familiarity with DoD AI strategies, MLOps, or data engineering in secure environments.
  • Previous experience supporting government agencies or military organizations. (NAVWAR, NIWC Pacific, or other Navy C2/ISR programs strongly preferred).

Education and Certification Requirements:

  • Bachelor of Science in Computer Science, Data Science, Geography, Math, Machine Learning, or Statistics, OR Equivalent years of relevant experience in lieu of a degree
  • Additional certifications in cloud, data engineering, GIS, or cybersecurity are a plus

Job Classification:

Associate II
$110,000 - $180,000

Disclaimer:

This job description in no way states or implies that these are the only duties to be performed by the employee(s) incumbent in this position. Employees will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities.

To perform this job successfully, the incumbents will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities.

This document does not create an employment contract, implied or otherwise, other than an at-will relationship.

An Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities