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

True Anomaly

Senior Machine Learning Engineer

Long Beach, CA · On-site

$114K - $156K/yr

They are seeking a Senior Machine Learning Engineer to design, build, and deploy machine learning and AI capabilities, working with a cross-functional team to enhance technology for space superiority.

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking ...

New

Cisco

Principal Machine Learning Engineer

Irvine, CA · On-site

$291K - $369K/yr

... machine-generated data - including logs, time series, traces, and events. We combine deep AI ... Partner with executive leadership, engineering, product, and data science teams to ensure AI ...

Masimo

Engineer II, AI/Machine Learning

Irvine, CA

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

Masimo

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

Masimo

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Orange, CA

Machine Learning Engineer information

See Orange, CA salary details

$33.6K

$137.6K

$206.7K

How much do machine learning engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for machine learning engineer in Orange, CA is $137,559.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,400.00 and $165,600.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 are the most commonly searched types of Machine Learning Engineer jobs in Orange, CA? The most popular types of Machine Learning Engineer jobs in Orange, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Orange, CA? For Machine Learning Engineer jobs in Orange, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Orange, CA look for? The top searched job categories for Machine Learning Engineer jobs in Orange, CA are:
What cities near Orange, CA are hiring for Machine Learning Engineer jobs? Cities near Orange, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Orange, CA as of June 2026, with employment types broken down into 98% Full Time, and 2% Part Time. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $137,559 per year, or $66.1 per hour.

Senior Machine Learning Engineer

True Anomaly

Long Beach, CA • On-site

$114K - $156K/yr

Full-time

Posted 27 days ago

Job description

Job Summary:
True Anomaly is a company focused on securing space through advanced technology. They are seeking a Senior Machine Learning Engineer to design, build, and deploy machine learning and AI capabilities, working with a cross-functional team to enhance technology for space superiority.
Responsibilities:
• Design, implement, and test ML/AI models that support threat assessment, object discrimination, and decision-making in operationally relevant environments
• Own the full ML development lifecycle — from data ingestion and feature engineering through model training, evaluation, and production deployment
• Collaborate with cross-functional teams to translate operational requirements into robust, production-ready ML capabilities
• Establish and maintain rigorous model evaluation practices to ensure reliability and performance in real-world conditions
• Write clean, well-documented, and testable code in support of AI/ML capabilities
Qualifications:
Required:
• Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a similar discipline
• Proficient in Python
• Solid understanding of statistics, probability, and optimization
• Experience with ML frameworks such as PyTorch, TensorFlow, or JAX
• 4+ years of experience designing, training, and deploying ML models in real-world systems
• Demonstrated ability to work in a multidisciplinary team and solve complex problems from first principles
• Passion for spaceflight and advancing capabilities related to space domain awareness and space security
• Work Location— this is a fully onsite role. Candidates must be based in or able to commute to our Denver or Long Beach office daily.
• Work environment—the work environment; temperature, noise level, inside or outside, or other factors that will affect the person's working conditions while performing the job.
• Physical demands—the physical demands of the job, including bending, sitting, lifting and driving.
• To conform to U.S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR) you must be a U.S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S.C. 1324b(a)(3), or eligible to obtain the required authorizations from the U.S. Department of State.
Preferred:
• Master's or PhD in machine learning, computer science, data science, or a related discipline
• Strong background in one of the following core ML disciplines: Anomaly & outlier detection: statistical, density-based, and deep learning approaches
• Strong background in one of the following core ML disciplines: Object discrimination: multi-class and fine-grained classification, metric learning, few-shot learning, evidential reasoning and Dempster-Shafer Theory (DST) for belief combination and conflict resolution under uncertain or incomplete sensor data
• Strong background in one of the following core ML disciplines: Unsupervised learning: clustering, dimensionality reduction, generative modeling
• Strong background in one of the following core ML disciplines: Sequential and temporal modeling: time-series analysis and sequential modeling
• Experience deploying models to edge or resource-constrained environments with real-time processing requirements
• Familiarity with space domain data such as space object catalog data, observational data, or RSO characterization
• Experience with MLOps tooling: experiment tracking (MLflow, W&B), model versioning, CI/CD for ML pipelines
• Background in model interpretability, uncertainty quantification, or safety-critical ML validation
Company:
True Anomaly develops space security technologies, including spacecraft, software platforms, and mission systems for orbital operations. Founded in 2022, the company is headquartered in Centennial, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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