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Machine Learning Operations Jobs in El Cajon, CA

iQuasar LLC

DATA SCIENTIST

San Diego, CA · On-site

$120K - $150K/yr

iQuasar is seeking to fill an Data Scientist/Machine Learning Engineerin San Diego, CA. At iQuasar ... Work alongside other AI/ML and DevOps engineers to establish automated AI workflows that ...

IQUASAR LLC

DATA SCIENTIST

San Diego, CA · On-site

iQuasar is seeking to fill an Data Scientist/Machine Learning Engineerin San Diego, CA. At iQuasar ... Work alongside other AI/ML and DevOps engineers to establish automated AI workflows that ...

G2IT

Lead Software & AI Engineer

San Diego, CA · On-site

$225K/yr

Demonstrated experience developing, integrating, or deploying Machine Learning (ML), Artificial Intelligence (AI), and/or Large Language Models (LLMs) within operational systems. * DoD 8140/8570 IAT ...

G2IT, LLC.

Lead Software & AI Engineer

San Diego, CA · On-site

$225K/yr

Demonstrated experience developing, integrating, or deploying Machine Learning (ML), Artificial Intelligence (AI), and/or Large Language Models (LLMs) within operational systems. * DoD 8140/8570 IAT ...

G2IT

Lead Software & AI Engineer

San Diego, CA

$225K/yr

Demonstrated experience developing, integrating, or deploying Machine Learning (ML), Artificial Intelligence (AI), and/or Large Language Models (LLMs) within operational systems. * DoD 8140/8570 IAT ...

Intuit

Manager 2, AI Science

San Diego, CA

$211K - $285K/yr

In this role you will be building and deploying machine learning models using both analytical ... Math, Econometrics, Operations Research, Physics, etc.) * 2+ plus years experience as an ...

Intuit

Manager 2, AI Science

San Diego, CA · On-site

$211K - $285K/yr

In this role you will be building and deploying machine learning models using both analytical ... Math, Econometrics, Operations Research, Physics, etc.) * 2+ plus years experience as an ...

General Atomics

Senior DevSecOps Engineer

Poway, CA · On-site

$106K - $146K/yr

... of machine learning systems * Work as part of an interdisciplinary team to productionize AI/ML models for air-to-air and air-to-ground combat operations * Develop and deploy scalable tools and ...

Trabus Technologies

Full Stack Engineer

San Diego, CA · On-site

$92K - $185K/yr

TRABUS works directly with end-users to build machine learning and full stack solutions from the ... s across diverse mission-focused projects. This is a great opportunity to build out new ...

Intuit

Manager 2, AI Science

San Diego, CA · On-site

$211K - $285K/yr

In this role you will be building and deploying machine learning models using both analytical ... Math, Econometrics, Operations Research, Physics, etc.) * 2+ plus years experience as an ...

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Showing results 41-60

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

Machine Learning Operations information

See El Cajon, CA salary details

$22

$41

$63

How much do machine learning operations jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for machine learning operations in El Cajon, CA is $41.65, according to ZipRecruiter salary data. Most workers in this role earn between $34.90 and $44.18 per hour, depending on experience, location, and employer.

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

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks among well-paying tech jobs.

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.

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

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

Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in El Cajon, CA as of June 2026, with employment types broken down into 2% As Needed, 42% Full Time, 54% Part Time, and 2% Temporary. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $86,624 per year, or $41.6 per hour.

Staff Software Engineer, Perception (R5421)

Shield AI

San Diego, CA • On-site

Full-time

Re-posted 5 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

The Hivemind Solutions Perception team develops the next generation of perception capabilities for autonomous systems by combining state-of-the-art machine learning with the proven foundations of computer vision. The team advances how autonomous platforms understand and interpret the world by developing vision, vision-language (VLM), and vision-language-action (VLA) models that tackle core perception challenges such as object understanding, scene interpretation, and mission-relevant environmental awareness. Working at the intersection of research and production, our engineers build the data pipelines, supervised fine-tuning (SFT) workflows, evaluation frameworks, and deployment infrastructure needed to transform cutting-edge AI research into reliable, mission-ready perception capabilities.
 
In this role, you'll lead the technical development of advanced machine learning solutions that define the future of perception for autonomous systems. You'll own the team's most challenging technical problems, drive architecture and model development across multiple efforts, and influence how foundation models are adapted, evaluated, and deployed for real-world autonomy. Working closely with researchers, perception engineers, autonomy engineers, and platform teams, you'll bridge cutting-edge AI research with scalable production systems while mentoring engineers and raising the technical bar across the organization.
What You'll Do:

Model Development – Design, train, fine-tune, and maintain state-of-the-art vision, vision-language, and vision-language-action models that improve perception and decision-making for autonomous systems. 

Data Pipelines & Model Training – Build scalable data pipelines, supervised fine-tuning (SFT) workflows, and evaluation loops that continuously improve model performance on mission-relevant tasks. 

Model Deployment & Optimization – Deploy and optimize machine learning models for embedded hardware using technologies such as ONNX, TensorRT, and hardware-accelerated inference frameworks. 

Perception & Autonomy Applications – Apply modern machine learning techniques to solve challenging perception and autonomy problems across aerial and other autonomous systems operating in complex, real-world environments. 

Research-to-Production – Translate cutting-edge machine learning research into production-ready capabilities by balancing model performance, robustness, computational efficiency, and operational reliability. 

Cross-functional Collaboration – Partner closely with perception, autonomy, platform, and software engineering teams to integrate machine learning capabilities into mission-ready autonomous systems. 

Model Evaluation & Validation – Develop benchmarks, testing methodologies, and evaluation frameworks to measure model performance, identify failure modes, and guide future improvements. 

Continuous Improvement – Improve training infrastructure, developer tooling, deployment workflows, and model lifecycle management to accelerate experimentation and production delivery. 

Required Qualifications:

  • Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience.

  • Expertise of machine learning fundamentals. 

  • Experience training an deploying ML models for computer vision in a production setting. 

  • Strong understanding of 3D vision problems/algorithms. 

  • Experience with machine learning frameworks such as PyTorch and TensorFlow. 

  • Demonstrated expertise in deploying models using TensorRT and ONNX. 

  • Proficiency in C++ and Python. 

  • Strong analytical and problem-solving skills, with the ability to translate research into practical applications. 

  • Ability to obtain a SECRET clearance 
Preferred Qualifications:

  • Experience with developing autonomous systems for defense customers. 

  • Experience with training/finetuning vision-language models, vision-language-action models, and/or world models.  

  • Contributions to open-source projects in machine learning or computer vision. 

  • Track record of publications in leading computer vision and robotics conferences and journals (e.g., CVPR, ICCV/ECCV, RAL, ICRA).

#LI-DS-1
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Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.