Looking for Python software engineers and backend/data developers for ongoing, 100% asynchronous remote contract work (up to $150+ USD/hr) evaluating, debugging, and benchmarking AI-generated Python code.

WHAT THE WORK INVOLVES:
• Testing and auditing AI-written Python implementations (backend logic, data pipelines, algorithms, asyncio, standard library & common frameworks)
• Catching subtle edge-case failures, mutability traps, off-by-one bugs, and O(n^2) complexity bottlenecks
• Writing clean, Pythonic reference solutions and explaining technical tradeoffs in clear English

COMPENSATION & LOGISTICS:
• Role setup: Freelance/contract work through Data Annotation Tech
• Pay: Up to $150+ USD/hr via PayPal
• Dashboard & payouts: Select projects from your dashboard that match your stack, submit your time worked after finishing each task, and withdraw funds a week later
• Schedule: 100% remote and completely asynchronous with no meetings, standups, or minimum weekly hours

WHAT WE LOOK FOR:
• Professional software engineering experience with Python (or an advanced CS / data / algorithmic coding background)
• Strong proficiency in Python (plus SQL, C++, TypeScript, Go, or Rust)
• Solid grasp of data structures, algorithms, and computational complexity (Big-O), plus strong written English

HOW TO APPLY:
Onboarding requires passing a one-time coding assessment. Because you only get a single attempt and experienced engineers often get tripped up by how the written explanations are graded, I'm happy to share a quick breakdown of what the graders look for along with the direct application for the programming track.

If you're interested (and don't already have an account on the platform), send me a DM with:
1. Your country of residence
2. Your software engineering experience & degree/education
3. Your primary programming languages and Python stack
4. Your comfort level with data structures, algorithms, and Big-O analysis
5. ~Weekly hours you have available for this work

Please leave a "DM Sent" comment on this post after messaging me so I know to check my message requests if Reddit hides your chat.

If you're building an application around YouTube data, one of the challenges is getting the information you need without having to handle every data collection step yourself.

I've been looking at the different use cases for YouTube data APIs, from channel research and video analytics to comment analysis and transcript-based applications. Here's a closer look at what you can do with the SteadyAPI YouTube API.

What data can you access?

Depending on the endpoint, you can use the API for tasks such as:

• Video details: Retrieve available metadata about individual videos, including titles, descriptions, and statistics.
• Channel information: Collect channel details to support creator research and channel monitoring.
• Video search: Find videos matching relevant keywords for content discovery and research.
• Comments: Retrieve available comments for audience research, feedback analysis, and content insights.
• Transcripts: Access available video transcripts for text analysis, summarization, and search indexing.
• Playlists and related videos: Explore video collections and discover related content where supported.

See the full endpoint details in the SteadyAPI YouTube API documentation.

What can you build with it?

1. YouTube analytics dashboards

Collect video and channel information to build dashboards that help users understand content performance and monitor available engagement metrics over time.

2. Creator research tools

Build workflows for researching channels, finding relevant videos, and organizing creators by topic or niche.

3. Comment analysis applications

Analyze available comments to identify recurring questions, common feedback, and audience interests. For larger datasets, consider pagination, storage, and request limits.

4. Content discovery platforms

Use video search and related content to help users find videos around particular subjects, keywords, or areas of interest.

5. Transcript search and AI workflows

Where transcripts are available, use them to power text search, summarization, topic extraction, or retrieval-augmented generation (RAG) systems.

6. Content monitoring

Periodically collect available public metrics and store timestamped snapshots to track changes. Historical trends require you to retain your own snapshots if historical records aren't provided by the endpoint.

Things to consider before integrating

• Endpoint coverage: Confirm that the API supports the specific data and operations your application requires.
• Request limits and pricing: Estimate your expected usage and review the applicable plan limits before running large jobs.
• Pagination: Plan for multiple requests when retrieving large result sets.
• Missing data: Comments may be disabled, and transcripts aren't available for every video.
• Caching: Store results where appropriate to reduce repeated requests and make your application more efficient.
• Error handling: Account for invalid identifiers, unavailable content, rate limits, and temporary failures.

Getting started

Visit the SteadyAPI YouTube API page to review the available endpoints and integration details. Before building a full application, test a few videos and channels that represent your actual use case, then verify the returned fields and request requirements.

What are you building with YouTube data? I'm curious whether people are mainly using it for analytics dashboards, creator research, comment analysis, or AI-powered applications.

Hi! I'm Davi, a junior full-stack developer from Brazil (Python, React, applied AI). I build small, practical automations that save businesses hours every week.

**What I can build for you**

- n8n workflows: form → CRM, lead routing, daily reports, Slack/Telegram/email notifications, simple AI steps (summaries, classification)

- API integrations between the tools you already use

- Python scripts to clean data and automate repetitive tasks

- Telegram and Discord bots

- Small React/front-end fixes

**Things I've built**

- An automated pipeline that runs daily on a cloud server and reports to Telegram (Node.js, scheduled jobs, AI calls)

- A custom Discord server bot

- Web projects in my portfolio below

**Rates**

- $20/hr, or a fixed price agreed in writing before I start

- Small automations usually land between $60 and $150

**How I work**

1. You tell me the problem; I reply with a short scope, price and deadline.
2. I build it, test it with you, and hand over a working, documented workflow.
3. Payment via PayPal or Wise.

**Portfolio:** https://davimonteles.vercel.app/

**GitHub:** https://github.com/Davi-Monteles

**English:** I read technical English comfortably and communicate in writing.

Send me a private message with what you need. Happy to give a quick estimate for free.

Hi

I'm an experienced automation & data extraction specialist offering:

• Custom web scraping & automation scripts
• B2B lead generation (targeted by niche & location)
• Data cleaning, formatting & enrichment
• Contact info extraction (emails, phone numbers, owners, etc.)

Why work with me?

• Fast delivery & top-notch quality
• You receive the complete source code for the automation/scraping projects
• Any business category in the U.S & Canada, EU and other countries

Let me help you save time & grow your business.

(Portfolio available on request)