Senior Software Engineer - Vector Search

As a Senior Software Engineer - Vector Search at AlphaSense, your main responsibilities will include building and enhancing our hybrid/vector search infrastructure, developing scalable backend services, and collaborating with various teams to deliver high-quality software solutions. You'll also take ownership of improving the reliability and performance of our search capabilities.

To qualify for the Senior Software Engineer - Vector Search position at AlphaSense, candidates typically need a BS, MS, or PhD in Computer Science or a related field, along with hands-on experience with vector search engines and 4+ years with open-source search technology. A strong programming background in Java or Python, plus familiarity with cloud platforms, is essential.

The work environment for a Senior Software Engineer - Vector Search at AlphaSense is dynamic and collaborative, encouraging innovation and employee growth. You’ll work with a diverse team of talented engineers focused on cutting-edge technology, contributing to a culture that values inclusion and the unique perspectives of each individual.

A Senior Software Engineer - Vector Search at AlphaSense should be proficient in Java and/or Python and have experience with vector search engines like Elasticsearch and hybrid search solutions. Familiarity with Kubernetes, Docker, and cloud platforms such as AWS or GCP is also important, as well as knowledge of IAC technologies like Terraform.

The typical salary range for a Senior Software Engineer - Vector Search at AlphaSense is between $150,000 and $230,000, depending on experience and location. In addition, candidates may be offered equity and a generous benefits program, reflecting AlphaSense’s commitment to attracting top talent.

Certainly! As a Senior Software Engineer, I have hands-on experience with various vector search engines, allowing me to effectively implement hybrid search solutions. I focus on understanding the underlying architecture and how different algorithms impact search relevancy, and I apply this knowledge when designing robust systems.

To ensure reliability and performance, I leverage monitoring tools to track system metrics and set up alerts for any anomalies. I also conduct regular code reviews and performance testing, and I utilize best practices such as load balancing and caching strategies to maintain the integrity of our services.

I implement strategies such as analyzing user query patterns, leveraging machine learning techniques for ranking, and continuous A/B testing of different algorithm variations. This iterative process allows me to refine and optimize the search experience based on user feedback and performance data.

I would begin by gathering requirements from stakeholders and users to deeply understand their needs. I’d then collaborate with product management and design teams to create a clear software architecture, and ensure that the backend services integrate seamlessly with our existing systems. Iterative development with feedback loops would be paramount during this process.

In a distributed system, I prioritize systematic troubleshooting which begins with identifying logs across services to pinpoint where the issue occurs. I utilize tracing tools to analyze requests flow, while also having a clear understanding of service dependencies, which helps me isolate issues effectively.

Teamwork is crucial in my development process. It fosters collaboration, encourages diverse input on designs, and promotes knowledge sharing. I regularly engage with cross-functional teams to align on goals, exchange ideas, and ensure everyone contributes to the project’s success.

I have extensive experience with cloud platforms, especially AWS and GCP. I’ve deployed applications using Kubernetes, managed container orchestration with Docker, and utilized various cloud services to enhance application performance and scalability in a cost-effective manner.

I actively follow industry blogs, participate in tech forums, and attend relevant webinars and conferences. Additionally, I enjoy engaging with the developer community through meetups and coding events, which helps me stay current with innovations and best practices in software engineering.

My experience includes tuning ranking algorithms by analyzing application data and user feedback. I have implemented machine learning models to improve search relevancy and have a strong understanding of how various factors influence a user’s search experience.

Creating an inclusive work environment is essential for innovation in tech. Diverse perspectives lead to better problem-solving and creativity. I advocate for open communication, respect, and opportunities for all team members to voice their ideas and contribute, regardless of background.