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Machine Learning Engineer Software Engineer Jobs in Richmond, CA

Machine Learning Engineer

San Francisco, CA · On-site +1

$172K - $384K/yr

Software Engineer, ML Platform - SlackMachine Learning, Optimization. Remote or Hybrid San Francisco, CA $150,000.00-$225,000.00 4 months ago Machine Learning Engineers (Open-Endedness) - Open Level ...

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Experience in software engineering with a focus on distributed systems and scalable backend ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build ... Experience in software engineering with a focus on distributed systems and scalable backend ...

We are building an AI-driven simulation software stack for engineering and manufacturing across ... Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ...

Working at the intersection of data science and software engineering, you translate R&D and project ... This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation ...

Strong background in algorithms, data structures, and software engineering principles. * Experience ... Deep understanding of state-of-the-art machine learning techniques and models. * Extensive industry ...

Strong foundation in machine learning and software engineering * Track record of building and owning ML systems in production where performance, reliability, or correctness materially mattered

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned ... Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and ...

Senior Machine Learning Engineer

San Francisco, CA · On-site

$144K - $190K/yr

About the Role Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasoned ... Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and ...

They are seeking a Machine Learning Engineer to contribute to the development of tools and ... software Founded in 2024, the company is headquartered in San Francisco, USA, with a team of 11-50 ...

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Machine Learning Engineer Software Engineer information

See Richmond, CA salary details

$72.9K

$169.3K

$235.8K

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

As of Jul 13, 2026, the average yearly pay for machine learning engineer software engineer in Richmond, CA is $169,309.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,700.00 and $198,500.00 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 job categories do people searching Machine Learning Engineer Software Engineer jobs in Richmond, CA look for? The top searched job categories for Machine Learning Engineer Software Engineer jobs in Richmond, CA are:
What cities near Richmond, CA are hiring for Machine Learning Engineer Software Engineer jobs? Cities near Richmond, CA with the most Machine Learning Engineer Software Engineer job openings:

Machine Learning Engineer

Happy Elements

San Francisco, CA

Full-time

Re-posted 5 days ago


Job description

Machine Learning Engineer
Full-time
Responsibilities
  • Build, maintain, and improve efficient and reliable data mining and machine learning models.
  • Design, implement and tune machine learning models, and provide performance feedback.
  • Work closely with data engineers to adapt and improve data pipelines for production models.
  • Work closely with software engineers in putting models into production (interface, SLA, scalability).Qualifications
  • Strong academic background required. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
  • Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow). Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
  • Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
  • Master with SQL or other relational database.
  • Master in building and productionizing end-to-end machine learning systems.
  • Knowledge and experience in cloud computing is a plus.
  • Extensive data modeling and data architecture skills.
  • Advanced math skills (linear algebra, Bayesian statistics, group theory).
  • Ability to consistently exercise independent discretion and judgment on significant matters.
  • Strong analytical, problem-solving and communication skills.
  • Ability to work in a team environment