KLUE ENGINEERING IS HIRING!

We’re looking for a Staff Engineer to join our ML Foundation and Platform team in Toronto, focusing on building and optimizing state-of-the-art LLM-powered agents that can reason, plan and automate workflows for users. You’ll be joining us at an exciting time as we reinvent our insight generation systems, making this an excellent opportunity for someone with strong Backend and ML fundamentals who wants to dive deep into practical LLM applications.

Q: WHAT EXPERIENCE ARE WE LOOKING FOR?

• Expertise in Python
• 5+ years of software engineering experience
• Proven experience leading large cross team initiatives
• 3+ years building and optimizing retrieval systems
• Deep understanding of LLMs, retrieval metrics and their trade-offs
• Experience implementing memory and tool-use strategies to enhance LLM-based agent capabilities
• Experience building end-to-end systems as a Platform Engineer, MLOps Engineer, or Data Engineer
• Strong understanding of software testing, benchmarking, and continuous integration
• Build scalable, production-ready ML pipelines for training, evaluation, deployment and monitoring
• Develop and implement CI/CD pipelines. Automate the deployment and monitoring of ML models.
• Knowledge of query augmentation and content enrichment strategies
• Expertise in automated LLM evaluation, including LLM-as-judge methodologies
• Skilled at prompt engineering - including zero-shot, few-shot, and chain-of-though.
• Proven ability to balance scientific rigor with driving business impact
• Track record of staying current with ML research and breakthrough papers

Q: WHAT MAKES YOU THRIVE AT KLUE?

A: We’re looking for builders who:

• Take ownership and run with ambiguous problems
• Jump into new areas and rapidly learn what’s needed to deliver solutions
• Bring scientific rigor while maintaining a pragmatic delivery focus
• See unclear requirements as an opportunity to shape the solution

As a member of our team, you’ll be leading the design and implementation of LLM-based agents, creating a platform for other teams to utilize ML capabilities and deploying ML services to production.
You’ll measure and improve retrieval systems across the spectrum from BM25 to semantic search and develop comprehensive evaluation metrics to measure their performance. You’ll work on building a platform for other teams to effectively utilize LLM tools and take advantage of prompt engineering.This includes developing APIs and scalable systems, developing scalable tools and services to handle machine learning training and inference for our clients, writing zero-shot and few-shot prompts with structured inputs/outputs, and implementing benchmarking systems for prompts. You will collaborate cross teams to identify LLM solution needs and shape the team’s technical roadmap
You will be responsible for building machine learning services and data pipelines to automatically extract insights about competitors from both public and internal data sources. Every day, our services process millions of data points, including news articles, press releases, webpage changes, Slack posts, emails, reviews, CRM opportunities, and user actions. You will maintain and develop services that utilize a broad array of ML techniques, including classification, clustering, recommendation, summarization, prompt engineering, vector search, RAG and agentic workflows.
You’ll work on building a platform for other teams to effectively utilize LLM tools and take advantage of prompt engineering. This includes developing APIs and scalable systems, developing scalable tools and services to handle machine learning training and inference for our clients, writing zero-shot and few-shot prompts with structured inputs/outputs, and implementing benchmarking systems for prompts.
Throughout all this work, you’ll apply your deep understanding of the latest breakthroughs to build scalable, production-ready systems that turn cutting-edge ML experiments into reliable business value.