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Machine Learning Engineer Software Engineer Jobs in Pasadena, CA

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling advanced software systems to automate Design for Manufacturing analysis. Responsibilities : • ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA · On-site

$250K/yr

By combining advanced software, robotics, and full-stack manufacturing, we are reinventing how ... As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling ...

Capgroup

Machine Learning Engineer II

Los Angeles, CA · On-site

$105K - $143K/yr

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production ...

Machina Labs

Machine Learning Engineer

Los Angeles, CA

$160K - $190K/yr

We build intelligent, software-defined factories that produce complex metal structures directly ... We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of ...

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

$150K - $180K/yr

Manage inputs gathered from unusual sources, including captures from software defined radio (SDR ... Bachelor degree with 4+ years experience as a machine learning engineer * AND 2+ years of Python ...

Capgroup

Senior Machine Learning Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

... Machine Learning Engineer at Capital Group" We are seeking a strong software engineer with ... We value craftsmanship in software engineering, thoughtful problem solving, and a strong sense of ...

Capital Group

Senior Machine Learning Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

... Machine Learning Engineer at Capital Group" We are seeking a strong software engineer with ... We value craftsmanship in software engineering, thoughtful problem solving, and a strong sense of ...

Motorola

Machine Learning Engineer

Los Angeles, CA

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director ... Develop software prototypes and integrate ML algorithms with Silvus' radio firmware and networking ...

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All JobsMachine Learning Engineer Software Engineer JobsMachine Learning Engineer Software Engineer Jobs in Pasadena, CA

Machine Learning Engineer Software Engineer information

See Pasadena, CA salary details

$69.3K

$160.9K

$224.2K

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

As of Jul 9, 2026, the average yearly pay for machine learning engineer software engineer in Pasadena, CA is $160,919.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,900.00 and $188,700.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Software Engineer vs Data Scientist?

AspectMachine Learning EngineerSoftware Engineer
Required CredentialsBachelor's/Master's in CS, specialized ML coursesBachelor's in CS or related field
Work EnvironmentDevelops ML models, algorithms, data pipelinesBuilds software applications, systems, APIs
Industry UsageAI/ML projects, data-driven solutionsWeb, mobile, enterprise software

Machine Learning Engineers focus on designing and deploying ML models, requiring expertise in algorithms and data handling. Software Engineers develop broader software applications, emphasizing coding and system architecture. While both roles require programming skills, ML Engineers specialize in AI/ML tasks, whereas Software Engineers work across various software domains.

How do Machine Learning Engineer Software Engineers typically collaborate with data scientists and software development teams?

Machine Learning Engineer Software Engineers often serve as a bridge between data scientists and software development teams. They work closely with data scientists to understand and implement machine learning models, ensuring that the models are production-ready and scalable. Additionally, they collaborate with software engineers to integrate these models into existing applications, monitor their performance, and address any engineering challenges. This cross-functional collaboration is essential for delivering robust, end-to-end AI solutions that add real value to the business.
What are popular job titles related to Machine Learning Engineer Software Engineer jobs in Pasadena, CA? For Machine Learning Engineer Software Engineer jobs in Pasadena, CA, the most frequently searched job titles are:
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What cities near Pasadena, CA are hiring for Machine Learning Engineer Software Engineer jobs? Cities near Pasadena, CA with the most Machine Learning Engineer Software Engineer job openings:
Machine Learning Engineer Software Engineer jobs near you

Machine Learning Engineer

V-Work Infotech Solutions INC

Cerritos, CA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary

We are seeking an experienced Machine Learning Engineer with 10+ years of software engineering or data engineering experience and strong expertise in designing, developing, deploying, and scaling machine learning solutions. The ideal candidate should have hands-on experience with Python, deep learning frameworks, MLOps, cloud platforms, data engineering, and Generative AI technologies.

The candidate will work closely with Data Scientists, AI Engineers, Data Engineers, and business stakeholders to build production-ready ML models and AI-powered applications.

Key Responsibilities
  • Design, build, and deploy machine learning models for production environments.
  • Develop predictive analytics, classification, regression, recommendation, and NLP models.
  • Build end-to-end ML pipelines for data ingestion, feature engineering, training, deployment, and monitoring.
  • Collaborate with Data Engineering teams to build scalable ML workflows.
  • Deploy ML models using Docker, Kubernetes, and cloud platforms.
  • Optimize model performance, scalability, and inference latency.
  • Implement CI/CD pipelines for machine learning (MLOps).
  • Work with structured and unstructured data from multiple sources.
  • Develop APIs for model serving and integration.
  • Monitor model drift, accuracy, and production performance.
  • Document technical designs and collaborate with cross-functional teams.

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