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Remote Python Engineer Jobs in San Francisco, CA

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

The Role We're looking for a Python Integrations Developer to own and expand the third-party ... Remote-first culture * Opportunity to grow with a scaling fintech company * Direct impact on client ...

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

The Role We're looking for a Python Integrations Developer to own and expand the third-party ... Remote-first culture * Opportunity to grow with a scaling fintech company * Direct impact on client ...

Nextracker

Forward Deployed Engineer (AI)

Fremont, CA · On-site +1

Forward Deployed Engineer (AI) Onsite - Fremont, California This position is required to be onsite in Fremont, California, and remote work arrangements are not being considered for this role.

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All JobsPython Engineer JobsRemote Python Engineer JobsRemote Python Engineer Jobs in San Francisco, CA

Remote Python Engineer information

See San Francisco, CA salary details

$27.1K

$164.9K

$238.6K

How much do remote python engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for remote python engineer in San Francisco, CA is $164,910.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,200.00 and $193,800.00 per year, depending on experience, location, and employer.

What does a remote Python engineer do?

A Remote Python Engineer designs, develops, and maintains software applications using the Python programming language, all while working from a remote location. Their responsibilities typically include writing efficient code, troubleshooting issues, collaborating with team members through online tools, and integrating third-party APIs or libraries. They may work on web development, automation scripts, data analysis, or backend services depending on the company's needs. Remote Python Engineers must have strong communication skills and be comfortable using project management and version control tools like Git. This role is ideal for those who want the flexibility of working from home while contributing to software projects.

What are the key skills and qualifications needed to thrive as a remote Python engineer, and why are they important?

To thrive as a Remote Python Engineer, you need a strong command of Python programming, experience with software development best practices, and familiarity with frameworks like Django or Flask, often supported by a relevant degree or equivalent experience. Proficiency in version control systems such as Git, cloud platforms like AWS or Azure, and continuous integration tools is typically required. Excellent problem-solving abilities, self-motivation, and clear written communication are crucial for effective collaboration in a remote environment. These skills ensure high-quality code delivery, efficient teamwork across distributed teams, and successful project outcomes.

What are some common challenges faced by remote Python engineers, and how can they be overcome?

Remote Python Engineers often encounter challenges such as effective communication across time zones, maintaining productivity outside a traditional office, and ensuring code quality in distributed teams. To overcome these, it's helpful to use collaborative tools like Slack and GitHub, participate in regular virtual meetings, and follow clear coding standards. Actively documenting your work and reaching out proactively to teammates can also foster a sense of connection and streamline project workflows.

What is the difference between Remote Python Engineer vs Remote Data Scientist?

AspectRemote Python EngineerRemote Data Scientist
Required SkillsPython, APIs, software developmentPython, statistics, machine learning
Work EnvironmentSoftware development teams, coding, debuggingData analysis, modeling, research
Industry UsageTech, startups, software companiesFinance, healthcare, tech

While both roles require Python skills, Remote Python Engineers focus on building and maintaining software applications, whereas Remote Data Scientists analyze data and develop models. The roles often overlap in Python proficiency but differ in their core responsibilities and industry applications.

What are the most commonly searched types of Python Engineer jobs in San Francisco, CA? The most popular types of Python Engineer jobs in San Francisco, CA are:
What are popular job titles related to Remote Python Engineer jobs in San Francisco, CA? For Remote Python Engineer jobs in San Francisco, CA, the most frequently searched job titles are:
What job categories do people searching Remote Python Engineer jobs in San Francisco, CA look for? The top searched job categories for Remote Python Engineer jobs in San Francisco, CA are:
What cities near San Francisco, CA are hiring for Remote Python Engineer jobs? Cities near San Francisco, CA with the most Remote Python Engineer job openings:
Remote Python Engineer jobs near you

Python Engineer (China or USA - Remote)

Braintrust

San Francisco, CA • Remote

$40 - $60/hr

Full-time

Posted 3 days ago

New

Job description

Company
Braintrust is a global talent network that connects top independent professionals with leading companies for high-quality, flexible work. We help organizations hire skilled talent faster while giving professionals access to vetted opportunities with innovative teams. 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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