Software Engineer, Web Crawling

As a Software Engineer specializing in Web Crawling at NewsBreak, your primary responsibilities include designing and deploying a real-time, adaptive web crawling infrastructure. You will develop strategies for dynamically prioritizing and indexing web pages based on user queries, collaborating closely with AI and recommendation teams. You'll also manage the full lifecycle of the crawling infrastructure to ensure performance and reliability.

To qualify for the Software Engineer, Web Crawling position at NewsBreak, candidates must possess a Bachelor's degree in Computer Science or a related field and have over 5 years of experience in large-scale web crawling infrastructure. Proficiency in distributed systems and system-level coding in languages like Python, Go, or C++ is also required, along with a familiarity with web technologies.

The Software Engineer, Web Crawling role is pivotal at NewsBreak as it involves developing an adaptive crawling system that rapidly indexes content based on real-time user interactions. Your work will enable the AI-driven systems to deliver fresh, localized content efficiently, improving user engagement and satisfaction.

Candidates should have extensive knowledge of web technologies, distributed systems, and web protocols (HTTP/HTTPS). Familiarity with anti-scraping countermeasures, JavaScript rendering, and experience in real-time user-driven crawling systems will also be advantageous for the Software Engineer, Web Crawling position at NewsBreak.

At NewsBreak, a Software Engineer specializing in Web Crawling can expect a competitive benefits package which includes comprehensive health coverage, a top-tier 401(K) plan with company matching, paid time off, and additional perks like a team activity budget, ensuring a well-rounded and fulfilling work experience.

Highlight your background in designing and operating web crawling infrastructure. Share specific projects where you managed high volumes of data efficiently, detailing the technologies and methodologies that contributed to your success.

Discuss a specific challenge, such as optimizing a crawling process or handling anti-scraping measures. Focus on the steps you took to analyze the problem, the solution you implemented, and the results of your approach.

Explain your approach to ensuring reliability, such as implementing robust error handling, utilizing monitoring tools, and employing profiling techniques to continuously improve system performance through feedback.

Discuss your favorite languages such as Python, Go, or C++, highlighting their strengths for developing crawling systems, including speed, support for libraries, and ease of maintenance in large-scale applications.

Describe techniques such as using headless browsers for JavaScript rendering or employing strategies to identify and fetch dynamically-generated content. Give examples of when you’ve successfully implemented these techniques.

Outline your optimization strategies, including the use of parallel processing, efficient state management, and tuning crawling protocols to ensure performance and lower latency.

Share your hands-on experience with developing crawling systems that feed data into AI pipelines. Discuss how you used user data to enhance recommendation systems and improve overall content accuracy.

Discuss your familiarity with HTTP/HTTPS and how understanding these protocols is essential for building effective crawling systems. You may include experiences related to performance tuning or overcoming limitations.

Talk about the resources you utilize, such as industry blogs, conferences, or community forums. Mention any continual learning efforts, such as courses or hands-on experimentation with new technologies.

Discuss algorithms used for URL prioritization based on factors like freshness, user query signals, and content relevance. Detail any experience with implementing these strategies effectively.