A suitable candidate will have solid Software Engineering skills with practical experience in integrating machine learning models in production workflows in both online and offline settings. Moreover, the candidate will also have solid experience in building and optimizing distributed systems that are able to leverage available compute and storage resources to build efficient applications for serving users.

We hire people motivated to solve the hard problems, keen to work in a larger team of data scientists and engineers, and ready to make a difference in how search and AI assistant landscape evolves.

Responsibilities:

• Design, implement, and ship AI-first product capabilities end-to-end from rapid prototype to production, spanning LLM-powered services, retrieval/grounding pipelines, and intelligent UX experiences.

• Design and execute offline and online experiments to assess product impact, iterating on techniques to improve models and maximize impact.

• Own implementation across the full stack integrating front-end experiences, back-end services, and AI orchestration layers that connect models, context, and tools to deliver cohesive, extensible, high-performance systems.

• Collaborate with design, research, and platform teams to adapt or fine-tune, optimize LLMs/SLMs models for real-world customer scenarios, ensuring outcomes are contextual, transparent, and human-centered.

• Build agentic, tool-using, and multimodal workflows that reason across data and services; optimize for safety, latency, reliability, and cost efficiency.

• Contribute to engineering excellence secure-by-design, accessibility compliance, automated testing, and code craftsmanship across the product lifecycle.

• Drive live-site reliability and operational excellence, participating in On-Call rotations while maintaining a sustainable, high-ownership engineering culture.

Qualifications:

• Bachelor's Degree in Computer Science, or related technical discipline with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

• Professional experience working with generative artificial intelligence, large language models or agent-based systems.

• Comfortable driving complex server and client architecture across large product teams.

• Hands-on experience with modern LLM evaluation techniques, including LLM-as-a-Judge, agentic evaluations and RAG assessments.

• A track record of delivering successful, large scale applied ML projects in an industry setting.

• Experience with MLOps practices, model versioning, automated testing, monitoring and CI/CD for machine learning.

• Cloud & Infrastructure: Skilled in building and operating infrastructure using Azure, AWS, or Google Cloud, and deploying containerized models with Docker, Kubernetes, or similar tools.

• Experience with proficient coding, debugging, and problem-solving skills.

• Excellent problem solving and data analysis skills.

• Outstanding communication and collaboration skills.

Preferred Qualifications:

• Master's Degree in Computer Science or related technical field with proven experience coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

• OR Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

• OR equivalent experience.

XML job scraping automation by YubHub