Staff Backend Engineer, AI/ML
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.
FAQQ: Klue who?
A: Klue is a VC-backed, capital-efficient growing SaaS company. Tiger Global and Salesforce Ventures led our US$62m Series B in the fall of 2021. We’re creating the category of competitive enablement: helping companies understand their market and outmaneuver their competition. We benefit from having an experienced leadership team working alongside several hundred risk-taking builders who elevate every day.
We’re one of Canada’s Most Admired Corporate Cultures by Waterstone HC, a Deloitte Technology Fast 50 & Fast 500 winner, and recipient of both the Startup of the Year and Tech Culture of the Year awards at the Technology Impact Awards.
Q: What are the responsibilities, and how will I spend my time?
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.
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
Q: What technologies do we use?
LLM platforms: OpenAI, Anthropic, open-source models
ML frameworks: PyTorch, Transformers, spaCy
Search/Vector DBs: Elasticsearch, Pinecone, PostgreSQL
MLOps tools: Weights & Biases, MLflow, Langfuse
Infrastructure: Docker, Kubernetes, GCP
Development: Python, Git, CI/CD
How We Work at Klue
Hybrid. Best of both worlds (remote & in-office)
Our main Canadian hubs are in Vancouver and Toronto. Ideally, this role would be located in Toronto.
You and your team will be in office at least 2 days per week.
Q: What about Compensation & Benefits
Competitive base salary
Benefits. Extended health & dental benefits that kick in Day 1
Options. Opportunity to participate in our Employee Stock Option Plan
Time off. Take what you need. Just ensure the required work gets done and clear it with your team in advance. The average Klue team member takes 2-4 weeks of PTO per year.
Direct access to our leadership team, including our CEO
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Not ticking every box? That’s okay. We take potential into consideration. An equivalent combination of education and experience may be accepted in lieu of the specifics listed above. If you know you have what it takes, even if that’s different from what we’ve described, be sure to explain why in your application.
At Klue, we're dedicated to creating an inclusive, equitable and diverse workplace as an equal-opportunity employer. Our commitment is to build a high-performing team where people feel a strong sense of belonging, can be their authentic selves, and are able to reach their full potential. If there’s anything we can do to make our hiring process more accessible or to better support you, please let us know, we’re happy to accommodate.
We’re excited to meet you and in the meantime, get to know us:
Pay Up For Progress & 50 - 30 Challenge
✅✅ Win-Loss Acquisition (2023)
Series B (2021)
Culture, culture, culture!
Winning as Women & More!
About Us
Product Demo Arena
Glassdoor
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☕️ LinkedIn
Wellfound (AngelList)
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