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Machine Learning Engineer Jobs in Foothill Ranch, CA

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

Qeexo, Co.

Data Engineering Intern

San Clemente, CA

$25/hr

As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a ... The Data Engineering Intern supports the development of scalable data systems and infrastructure ...

Qeexo, Co.

Data Engineering Intern

San Clemente, CA

$25/hr

As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a ... The Data Engineering Intern supports the development of scalable data systems and infrastructure ...

FieldAI

Software Engineer, MLOps

Irvine, CA · On-site

The MLOps Engineer will design and maintain infrastructure for machine learning systems, collaborating closely with engineering teams to ensure effective deployment and monitoring of ML models.

Deloitte

Senior AI Engineer - SFL Scientific

Costa Mesa, CA · On-site

$112K - $154K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Qeexo, Co.

Data Engineering Intern

San Clemente, CA · On-site

$25/hr

As a pioneer in automated machine learning for edge devices and a subsidiary of TDK Corporation, a ... The Data Engineering Intern supports the development of scalable data systems and infrastructure ...

Turion Space

Lead AI Engineer

Irvine, CA

$110K - $144K/yr

Description The Lead AI Engineer will be responsible for defining and driving the AI strategy ... Design, develop, and deploy advanced AI models and algorithms, including machine learning, deep ...

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Showing results 41-60

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Foothill Ranch, CA

Machine Learning Engineer information

See Foothill Ranch, CA salary details

$32.5K

$133K

$199.9K

How much do machine learning engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning engineer in Foothill Ranch, CA is $133,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,900.00 and $160,100.00 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 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 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 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 cities near Foothill Ranch, CA are hiring for Machine Learning Engineer jobs? Cities near Foothill Ranch, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Foothill Ranch, CA as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $133,025 per year, or $64 per hour.

Senior Software Engineer, MLOps

FieldAI

Irvine, CA • On-site

$131K - $173K/yr

Full-time

Re-posted 23 days ago

Job description

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.
We are seeking a skilled and motivated Senior MLOps Engineer to join our engineering team. In this role, you will design and maintain the infrastructure and tooling that supports the full lifecycle of machine learning systems used in robotics applications. You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an exciting opportunity to help operationalize machine learning in real-world robotic systems within a fast-growing and dynamic environment.
What You Will Get To Do
  • Design, build, and maintain GPU based infrastructure for machine learning pipelines, including data processing, training, evaluation, inference and deployment workflows.
  • Collaborate closely with robotics teams to implement model serving infrastructure for edge/robot deployment.
  • Build tools and automation to support reproducible experiments, model versioning, and dataset management.
  • Deploy and manage ML services and inference pipelines using containerized environments for efficient scaling and scheduling of heterogeneous compute resources.
  • Monitor model performance and system reliability across development and production environments.
  • Improve the efficiency, scalability, and reliability of ML workflows and infrastructure.
  • Work with cross-functional engineering teams to integrate ML components into robotics software systems.

What You Have
  • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent work experience).
  • 3-7 years of experience in MLOps, machine learning infrastructure, or related engineering roles.
  • Strong programming skills in Python or similar languages.
  • Experience building and maintaining machine learning pipelines.
  • Hands-on experience with cloud and cloud-native tools such as AWS (SageMaker, S3, or similar cloud ML services), Kubernetes etc.,
  • Solid understanding of Linux systems and distributed computing environments.
  • Experience with GPU workload scheduling and orchestration across multi-region cloud environments.
  • Excellent problem-solving skills and the ability to work collaboratively in a team environment.

What Will Set You Apart
  • Experience deploying and operating ML systems for robotics or real-world physical systems.
  • Experience with scaling AI, ML, and inference workloads on Kubernetes.
  • Exposure to ROS-based robotics data formats and pipelines (rosbags, point clouds)
  • Experience with experiment tracking, model versioning, or dataset versioning tools.
  • Experience optimizing ML pipelines for large-scale training and data processing.
  • Experience working closely with research or applied machine learning teams.

Compensation and Benefits
Our salary range is competitive with the market, but we take into consideration an individual's background and experience in determining final salary; base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. Also, while we enjoy being together on-site, we are open to exploring a hybrid or remote option.
Why Join Field AI?
We are solving one of the world's most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment.
You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.
Be Part of the Next Robotics Revolution
To tackle such ambitious challenges, we need a team as unique as our vision - innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We're seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.
We are headquartered in always-sunny Irvine, Southern California and have US based and global teammates.
Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!
We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.
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.

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