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Machine Learning Engineer Software Engineer Jobs in Richmond, CA

MrBeast

Senior Machine Learning Engineer

San Mateo, CA · Hybrid

$119K - $163K/yr

Senior Machine Learning Engineer Primary: Bay Area (San Francisco / Peninsula) | Secondary: NYC The ... Partner with product, data scientists, and software engineers to define and ship ML solutions.

Kikoff

Senior Machine Learning Engineer

San Francisco, CA · On-site

$123K - $169K/yr

The ideal candidate will have a strong background in software development, machine learning, and data engineering, with experience in deploying scalable ML models in production environments. Key ...

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... machine learning engineers. We are looking for developers who are excited about staying at the ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Hive also offers turnkey software applications powered by proprietary AI models and datasets ... machine learning engineers. We are looking for developers who are excited about staying at the ...

Orchard

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will develop solutions for machine learning and computer vision software, working with large datasets to improve agricultural efficiency and sustainability.

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147K - $194K/yr

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine ... Collaborate closely with ML scientists and software engineers to understand current challenges and ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Eve

Machine Learning Engineer

San Mateo, CA · On-site

We're hiring an Machine Learning Engineer as the volume and complexity of legal AI workflows in our system scale rapidly. As more firms rely on Eve to automate high-stakes legal work - from intake ...

Ema

Software Engineer, Machine Learning

San Francisco, CA · On-site

$160K - $220K/yr

Who You Are We're looking for innovative and passionate Machine Learning Engineers to join our team ... Good understanding of software development principles, data structures, and algorithms. * Excellent ...

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

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 Aug 11, 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 Software Engineer jobs near you

Senior Machine Learning Engineer

MrBeast

San Mateo, CA • Hybrid

$119K - $163K/yr

Full-time

Re-posted 24 days ago

Job description

Senior Machine Learning Engineer

Primary: Bay Area (San Francisco / Peninsula)   |   Secondary: NYC

The Opportunity

We're doing an AI-first engineering rebuild for a company that already has an audience of 100M+ people. This is a zero-to-one build with no legacy constraints, so you get to stand up ML systems the right way from day one. You're here to ship machine learning that creates real, measurable value for a massive consumer audience.

The Product

You'll design, build, deploy, and operate ML systems that power the MrBeast ecosystem, bridging data science, software engineering, and platform engineering to ship production-grade capabilities. That means:

  • Build scalable ML systems and services that move real business metrics for an audience of 100M+ people.
  • Own the full lifecycle: pipelines for data processing, feature engineering, training, validation, deployment, and monitoring.
  • Set the bar for AI-first engineering, including how we test new model capabilities and bring them into production.

What You'll Do

  • Design and implement scalable ML systems and services for production.
  • Develop, evaluate, and optimize models against real business problems.
  • Build and maintain ML pipelines across data processing, features, training, validation, and deployment.
  • Establish monitoring, observability, and model-performance tracking.
  • Partner with product, data scientists, and software engineers to define and ship ML solutions.
  • Drive architecture decisions for ML infrastructure and platform capabilities, and cut deployment cycle time.
  • Mentor engineers, set best practices, and make sure systems meet security, reliability, and compliance bars.

Who You Are

  • AI-Native: You live and breathe this: you're already burning through tokens daily, and shipping ML is the job itself.
  • Production ML Builder: Typically 8+ years in software or ML engineering, with strong experience deploying and operating ML systems in production and solid Python and software engineering practice.
  • Systems Thinker: You've designed scalable distributed systems and data-intensive applications, and you know why a model that looks great offline can fail in production.
  • Evidence-Driven Owner: You decide with experimentation and measurable results, and you own outcomes from design through production operation.

Bonus points for MLOps platforms and automated model lifecycle management, cloud-native ML architectures and distributed training, responsible AI and model governance, and leading technical initiatives across multiple teams.

Benefits

  • Equity: Highly competitive equity package designed for a foundational hire.
  • Hybrid Model: Expected ~3 days per week in-office (Bay Area or NYC).

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