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Python Contractor Jobs in San Francisco, CA (NOW HIRING)

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Python Contractor information

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$15

$69

$101

How much do python contractor jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for python contractor in San Francisco, CA is $69.07, according to ZipRecruiter salary data. Most workers in this role earn between $56.92 and $78.46 per hour, depending on experience, location, and employer.

What is a Python contractor?

A Python Contractor is a professional software developer who specializes in Python programming and works on a contract basis rather than as a full-time employee. They are typically hired for specific projects or a set period to develop, test, and maintain Python-based applications. Python Contractors often work remotely or on-site, collaborating with teams to build web applications, data analysis tools, automation scripts, and more. Their responsibilities depend on the industry and project requirements, and they may be engaged by startups, enterprises, or agencies.

What are the key skills and qualifications needed to thrive as a Python contractor?

To thrive as a Python Contractor, you need strong programming skills in Python and related frameworks, experience with software development best practices, and a relevant degree or proven project track record. Familiarity with tools like Git, Docker, cloud platforms (such as AWS or Azure), and certifications in Python or software development are often advantageous. Strong communication, problem-solving abilities, and adaptability help differentiate top contractors in dynamic team environments. These skills and qualities are essential to deliver reliable, maintainable solutions while efficiently collaborating with stakeholders and adapting to varying client requirements.

What types of projects do Python contractors typically work on and what does a typical workday look like?

Python Contractors often work on a diverse range of projects, including web application development, data analysis, automation scripts, and integrating APIs for clients across different industries. A typical workday may involve coding, debugging, reviewing requirements with clients or team members, and collaborating via project management tools or version control systems. Contractors usually need to manage their time efficiently, communicate progress clearly, and deliver solutions that meet specific client needs and deadlines. The work can be remote or on-site, often involving close collaboration with other developers, project managers, or data analysts.

What are the most commonly searched types of Python Contractor jobs in San Francisco, CA? The most popular types of Python Contractor jobs in San Francisco, CA are:
What are popular job titles related to Python Contractor jobs in San Francisco, CA? For Python Contractor jobs in San Francisco, CA, the most frequently searched job titles are:
What job categories do people searching Python Contractor jobs in San Francisco, CA look for? The top searched job categories for Python Contractor jobs in San Francisco, CA are:
What cities near San Francisco, CA are hiring for Python Contractor jobs? Cities near San Francisco, CA with the most Python Contractor job openings:
Python Contractor jobs near you
Infographic showing various Python Contractor job openings in San Francisco, CA as of August 2026, with employment types broken down into 70% Full Time, 9% Part Time, and 21% Contract. Highlights an 88% Physical, 1% Hybrid, and 11% Remote job distribution, with an average salary of $143,658 per year, or $69.1 per hour.

Python Engineer (China or USA - Remote)

Braintrust

San Francisco, CA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

About this role

As a Senior Python Engineer, you will work remotely on an hourly paid basis to review AI-generated Python solutions and technical explanations, as well as generate high-quality reference content that demonstrates strong software engineering practices. You will assess solutions for correctness, code quality, performance, and adherence to the prompt; identify errors in logic, architecture, or methodology; fact-check technical information; craft clear, step-by-step explanations and exemplary solutions; and rate and compare multiple AI responses based on their reasoning quality and implementation soundness. This is a fully remote, hourly paid contractor role with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world’s largest AI companies and foundation model labs, where your Python expertise will directly help improve the world’s premier AI models.

Your profile
  • Bachelor’s degree or higher in Computer Science, Software Engineering, Mathematics, or a closely related technical field.
  • 7+ years of professional software engineering experience, with significant hands-on work in Python on production systems.
  • Deep knowledge of Python language features, the standard library, and common ecosystems such as web frameworks, data tooling, or backend services.
  • Strong understanding of algorithms, data structures, system design, and performance optimization in Python applications.
  • Proven experience designing, reviewing, and improving high-quality Python codebases, including code review and mentoring responsibilities.
  • Minimum C1 English proficiency (written and spoken), with the ability to write clear technical explanations and follow detailed English-language guidelines.
  • Comfort working with modern tooling such as version control systems, CI/CD pipelines, testing frameworks, and containerization technologies.
  • Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus.
  • Highly detail-oriented, with a structured and methodical approach to evaluating reasoning quality and identifying subtle errors in technical solutions.
  • Minimum C1 Chinese proficiency (written and spoken)
Key responsibilities
  • Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
  • Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
  • Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.


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