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

Senior Machine Learning Engineer

San Diego, CA ยท On-site

$171K - $231K/yr

Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping conceive, code, and deploy AI science models at scale using the latest industry tools. As a Senior engineer ...

Overview Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping conceive, code, and deploy AI science models at scale using the latest industry tools. As a Senior ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

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 ยท On-site

$180K - $250K/yr

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 ยท On-site

$180K - $250K/yr

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 ...

Showing results 21-40

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.

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.

Senior Machine Learning Engineer

Murata Manufacturing Co., Ltd.

San Diego, CA โ€ข On-site

$140 - $178/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


Key responsibilities

  • Design and develop advanced machine learning models for radar signal processing.

  • Evaluate novel ML and deep learning architectures for radar data and develop end-to-end ML pipelines.

  • Analyze and model raw and processed radar data to support product development and performance optimization.


Job description

Sensoride has been driven by a simple vision - to make sensing smarter, faster, and more reliable. We create innovative technologies that help industries see and understand the world with unmatched clarity. From improving safety on the road to enabling the next generation of intelligent radar sensors, our solutions turn emerging ideas into reality.

Every day, we push the boundaries of what's possible, because we believe precision matters in mobility. The breakthroughs we're making today are shaping the smarter, safer, and more accurate sensors - and wherever accuracy matters, you'll find Sensoride at the center.

Why Consider This Job Opportunity

The Senior Machine Learning Engineer works on meaningful, real-world challenges where machine learning directly impacts the performance of automotive radar sensing products. This position works alongside a talented team developing cutting-edge technologies.

Workplace Policy

On-site from San Diego, CA.

After hours support and coverage are required.

What To Expect (Essential Job Responsibilities)
  • Design and develop advanced machine learning models for radar signal processing.
  • Evaluate novel ML and deep learning architecture for radar data.
  • Develop end-to-end ML pipelines, including data preprocessing, feature extraction, model training, validation, and performance optimization for radar data.
  • Analyze and model raw and processed radar data (e.g., time-domain, frequency-domain, range-Doppler, range-angle representations).
  • Drive innovation by evaluating and implementing state-of-the-art ML and deep learning techniques for radar-based detection, classification, and tracking.
  • Optimize models for real-time and embedded deployment, considering constraints such as latency, memory, and power.
  • Bridge theory and practice by translating research outcomes into scalable, real-world applicable algorithms.
  • Support product development through algorithm validation, performance benchmarking, and documentation.
  • Strong statistical and mathematical skills to act as the in-house mathematician/statistician.
  • Review and provide feedback on technical designs, research reports, and algorithm implementations.
  • Represent the team or organization in internal technical forums, design reviews, and external workshops.
  • Ensure adherence to best practices in research methodology, data management, and experimental reproducibility.
  • Assist in defining coding standards, evaluation metrics, and benchmarking methodologies.
  • Promote knowledge sharing through documentation and training sessions.
  • Support hiring activities, including technical interviews and candidate evaluation.
What Is Required (Qualifications)
  • Master's or PhD in Applied Mathematics, Statistics, Electrical Engineering, Computer Science, or a related field.
  • 3+ years' research experience in developing machine learning models and applied statistics.
  • After hours support and coverage are required.
  • Strong understanding of radar fundamentals and signal processing concepts.
  • Proven experience applying ML/DL techniques (e.g., CNNs, RNNs, Transformers, classical ML) to radar or similar sensing modalities.
  • Proficiency in Python and ML frameworks such as PyTorch or TensorFlow; experience with data analysis tools (NumPy, SciPy, pandas).
  • Ability to train, build, deploy, and manage machine learning models for radar applications such as Google Colab, AWS, or similar platforms.
  • Problem-solving skills with the ability to work across multidisciplinary teams.
  • Strong communication skills with the ability to explain complex technical concepts clearly.
How To Stand Out (Preferred Qualifications)
  • Experience applying machine learning to radar, perception, robotics, or autonomous systems.
  • Deep understanding of signal processing and sensor data analysis.
  • Proven track record of designing ML models that deliver measurable product impact.
  • Experience with time domain samples, data augmentation and field testing.
  • Publications, patents, or noteworthy technical contributions in ML or sensing technologies.
  • Curiosity, ownership, and a passion for building cutting-edge products with a high-performing team.
Other

Minimum Salary: $140,000

Maximum Salary: $178,000

We consider various factors in determining actual pay including your skills, qualifications, and experience. In addition to salary, this position is eligible for incentive awards based on individual and business performance as well as competitive benefits.

  • Comprehensive benefits package including medical, dental, and vision insurance.
  • Generous Paid Time Off including paid holidays and floating holidays.
  • 401(k) employer match on retirement planning.
  • Hybrid working schedule for eligible positions.
  • Tuition reimbursement on approved programs.
  • Flexible and health spending accounts.

Sensoride offers competitive compensation and comprehensive benefits.
Equal Opportunity/Affirmative Action Employer -M/F/Disabilities/Veteran s

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