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Hourly Python Contractor Jobs in New York (NOW HIRING)

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... 2 hourly basis or $77.00 per hour on a Corp basis. The Corp rate is for independent contractors ... Python, or cloud data platforms (Azure/AWS) Experience with data ingestion frameworks, ETL/ELT ...

Hourly Python Contractor information

What is the difference between Hourly Python Contractor vs Python Developer?

AspectHourly Python ContractorPython Developer
CredentialsTypically no formal certification required, but experience and portfolio matterOften holds a degree in computer science or related field, certifications like PCEP or PCAP are common
Work EnvironmentFreelance, project-based, remote or on-siteFull-time or part-time employment, usually in an office or remote
Employer UsageHired for specific projects or short-term tasksPart of a company's development team, involved in ongoing projects
Search & Comparison IntentLooking for flexible, short-term Python workSeeking full-time or long-term Python development roles

Hourly Python Contractors are typically freelancers hired for specific projects without formal employment, while Python Developers are usually employed full-time within organizations. Both roles require Python skills, but their work arrangements and commitments differ significantly.

What cities in New York are hiring for Hourly Python Contractor jobs? Cities in New York with the most Hourly Python Contractor job openings:

Python Engineer (China or USA - Remote)

Braintrust

Manhattan, NY • On-site

Other

This job post has expired today. 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.