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Contract Google Machine Learning Engineer Jobs in Santa Rosa, CA

Deep understanding of modern machine learning and deep learning techniques * Experience training ... Engineering, Model Training, Distributed Training, Pretraining, Fine-Tuning, Post-Training ...

Deep understanding of modern machine learning and deep learning techniques * Experience training ... Engineering, Model Training, Distributed Training, Pretraining, Fine-Tuning, Post-Training ...

Software Engineer, DevOps

Bodega Bay, CA · On-site

$135K - $225K/yr

Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers ... Experience with event-driven data and machine learning infrastructure, including streaming ...

For3+ years of software engineering experience, with meaningful exposure to AI or machine learning produ * ctsStrong Python skills and experience building backend syst * emsHands-on experience ...

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Contract Google Machine Learning Engineer information

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How much do contract google machine learning engineer jobs pay per hour?

As of Jun 17, 2026, the average hourly pay for contract google machine learning engineer in Santa Rosa, CA is $53.50, according to ZipRecruiter salary data. Most workers in this role earn between $44.95 and $55.43 per hour, depending on experience, location, and employer.
What job categories do people searching Contract Google Machine Learning Engineer jobs in Santa Rosa, CA look for? The top searched job categories for Contract Google Machine Learning Engineer jobs in Santa Rosa, CA are:
What cities near Santa Rosa, CA are hiring for Contract Google Machine Learning Engineer jobs? Cities near Santa Rosa, CA with the most Contract Google Machine Learning Engineer job openings:
Staff Machine Learning Engineer, Credit Products (Square Financial Services)

Staff Machine Learning Engineer, Credit Products (Square Financial Services)

Block

Bodega Bay, CA • On-site

Other

Posted 2 days ago


Block rating

7.9

Company rating: 7.9 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

9th of 17 rated payment service providers


Job description

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams - People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more - provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

The Role

The Credit and Lending team is responsible for the predictive intelligence that underpins Block's primary capital-intensive products. These products unlock unique access to credit for our customers, many of whom are otherwise underbanked and underserved by the traditional financial system. As a Machine Learning Engineer within Square Financial Services (SFS), you will occupy a high-leverage role at the intersection of regulated banking and advanced autonomous systems. This position requires full-stack ownership of the credit engine, from the curation of novel data signals to the implementation of the decisioning logic that drives Block's top-line growth.
Our credit products are material drivers of the company's profitability and are frequently highlighted in executive reviews and quarterly earnings reports. We are seeking a scientifically-minded contributor capable of delivering extraordinary individual leverage to expand our underwriting capabilities into previously untapped segments through pragmatic policy evolution and advanced modeling techniques.

You Will

  • Apply a rigorous scientific mindset to the challenge of underwriting new customer segments, involving the evaluation of alternative external data sources and the deployment of advanced architectures to enhance predictive accuracy.
  • Lead complex ML Operations and Infrastructure initiatives that advance our modeling capabilities, such as scaling data ingestion or enabling the use of more complex neural networks.
  • Design and implement the full credit modeling stack, taking responsibility for the entire lifecycle of credit decisioning and ensuring models are robustly integrated into production environments.
  • Use data science techniques to leverage new data sources for modeling, making sense of messy datasets and bringing clarity to business decisions.
  • Identify and execute material improvements to credit policy, applying an analytical lens to determine where technical or logic shifts can yield significant positive outcomes for the customer and the bank's portfolio.
  • Support team members in ad-hoc and scheduled updates to existing models, and help troubleshoot issues in a real-time production environment.
  • Operate effectively within the framework of a regulated bank (SFS), balancing rapid innovation with the requirements of safety, soundness, and compliance.

You Have

  • Minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years experience, with a focus on developing and deploying machine learning and statistical models in production environments.
  • A degree in a technical field (e.g., Computer Science, Mathematics, Statistics, Physics, or Engineering). We have a strong preference for candidates with a demonstrated track record of scientific research or an advanced degree.
  • Strong quantitative intuition and data visualization skills, with a proven ability to conduct sophisticated ad-hoc and exploratory analysis.
  • Full-stack proficiency preferred, including the ability to contribute across the entire technical stack-from data pipelines to production-grade software architecture.
  • The versatility to communicate clearly with both technical and non-technical audiences, particularly in the context of high-visibility projects and executive stakeholders.
  • A pragmatic approach to problem-solving, with a willingness to utilize whichever tool is most appropriate for the situation while balancing complex business, technical, and regulatory constraints.
  • Experience with tree-based models and gradient boosting is helpful but not required; we value the ability to adapt and learn new methodologies as the credit landscape evolves.

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we're doing to build a workplace that is fair and square? Check out our I+D page.


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