Senior Software Engineer, Search

As a Senior Software Engineer on the Search team at Cohere, your primary responsibilities will include building and optimizing a next-generation search platform that combines traditional information retrieval methods with modern AI techniques. You'll integrate advanced models into our retrieval products, design and maintain document ingestion pipelines for various data types, and extend Kubernetes manifests for scalable deployments. Collaborating effectively with internal teams and external partners will be key to ensuring the success and functionality of our search solutions.

For the Senior Software Engineer position at Cohere, you should have a strong background in Python programming and experience in developing and maintaining API services. Familiarity with search or recommendation systems, whether using classical IR techniques or modern ML methods, is also important. Additionally, a solid understanding of distributed systems, cloud-native deployments, and performance optimization in high-volume systems will further enhance your fit for this role.

Senior Software Engineers at Cohere work with a variety of technologies in the search domain, including classical information retrieval methods like BM25 and modern AI tools for semantic search. You’ll also work with Kubernetes, Helm charts, Terraform for cloud-native deployments, and platforms like OpenSearch to experiment with indexing and nearest neighbor search strategies. A strong grasp of distributed systems will also play a vital role in your work.

Absolutely! Collaboration is at the heart of the Senior Software Engineer role on the Search team at Cohere. You'll work closely with Machine Learning Engineers and Research Scientists to integrate state-of-the-art models into retrieval systems, while also engaging with various teams across the organization to tackle search challenges and create successful outcomes for both internal and external stakeholders.

Cohere fosters a vibrant and inclusive work culture where diversity and passionate collaboration are celebrated. As a Senior Software Engineer, you’ll be part of a team that values innovation and works hard to achieve a common goal – advancing AI for humanity. We encourage open communication, creative problem-solving, and a healthy work-life balance, ensuring that every team member feels valued and supported in their endeavors.

In answering this question, you should demonstrate your knowledge of classical information retrieval methods like BM25 while highlighting how you would integrate modern AI models. Discuss your approach to evaluating different algorithms, focusing on their strengths and weaknesses, and share your experiences using both in past projects.

It's important to provide specific examples of your experience with cloud-native deployments, including any tools and technologies you’ve used, such as Kubernetes and Terraform. Mention how these experiences have shaped your understanding of scalability, high availability, and resource optimization in a cloud environment.

When answering this question, be detailed about the problem, the steps you took to troubleshoot and resolve it, and the ultimate outcomes of your solution. Discuss the importance of collaborating with others during this process and what you learned from the experience.

Focus on best practices like writing clean, modular code, using version control, and rigorous documentation. Discuss the importance of testing and performance optimization, and share techniques you follow to review and refactor code for long-term maintainability and scalability.

Answer this by emphasizing the significance of teamwork in problem-solving and innovation within software engineering. You can mention how collaborating with cross-functional teams helps in bringing diverse perspectives into the decision-making process, ultimately leading to better product outcomes.

Respond with a structured approach to incident management, including identifying the issue, rolling back if necessary, and collaborating with team members to analyze the root cause. Emphasize your commitment to learning from failures and sharing those lessons with the team to prevent future occurrences.

Highlight specific projects where you have designed or implemented search technologies. Discuss the challenges you faced and the techniques you used, whether they were classical IR methods or AI-driven strategies. Mention any tools or platforms you've utilized in these projects.

Explain your understanding and experience creating and maintaining document ingestion pipelines, and share examples of the types of data you've worked with. Discuss your strategy for ensuring data integrity, consistency, and efficiency in the pipeline process.

When prioritizing features, stress the importance of user feedback and business goals. Explain how you approach aligning technical capabilities with user needs, utilizing techniques like value-vs-effort analysis to decide which features to implement first.

Discuss specific techniques such as caching, indexing strategies, and algorithm tuning that you've employed to improve search performance. Provide examples of how you measured success, such as response times and user engagement metrics.