×
Register Here to Apply for Jobs or Post Jobs. X

Software Engineer, AI

Job in Toronto, Ontario, C6A, Canada
Listing for: Klue
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Engineer
Job Description & How to Apply Below
Klue Engineering is hiring!
We're looking for a  Machine Learning Engineer  to join our 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.

FAQ
Q:
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  search and retrieval agent  systems that enable users to discover high-quality, relevant information with minimal effort. You will work at the intersection of  LLM-powered agent workflows, retrieval pipelines, and evaluation frameworks , ensuring that our systems remain scalable, efficient, and aligned with user intent.

On a day to day basis you will:

Design and implement  retrieval-augmented generation (RAG) systems with agentic workflows  to refine  query understanding, document retrieval, and response synthesis .

Build and optimize retrieval pipelines using  BM25, dense retrieval, hybrid retrieval, and re-ranking  approaches.

Develop evaluation pipelines for retrieval and generation, including  offline metrics (recall, MRR, nDCG) and human-in-the-loop evaluations .

Experiment with  query rewriting, expansion, and classification  to improve retrieval relevance.

Collaborate closely with Product to bring ML-powered search agents into production.

Profile, debug, and optimize the latency, accuracy, and scalability of retrieval and generation components.

Contribute to the design of data pipelines for training retrieval and ranking models, including dataset curation, augmentation, and labeling workflows.

Stay up-to-date with advancements in LLMs, retrieval techniques, and agent architectures, evaluating opportunities to integrate them into our systems.

Q:
What experience are we looking for?

5+ years of software engineering experience

Experience with  information retrieval systems , search relevance, and ranking models

Expertise in Python, with experience in frameworks such as PyTorch, Tensor Flow, or JAX.

Familiarity with  LLMs, prompt engineering, and retrieval-augmented generation pipelines .

Understanding of evaluation methods for search systems, including offline metrics and user-facing evaluation.

Experience working with  vector database infrastructure (FAISS, Milvus, Weaviate, Pinecone, PGVector)  and traditional search engines (Elasticsearch, Open Search)

Understanding of  data pipelines, preprocessing, and large-scale data handling .

Ability to work independently and collaboratively in a fast-paced environment, balancing research and production needs.

Develop and implement CI/CD pipelines. Automate the deployment and monitoring of ML models.

Knowledge of  query understanding, document summarization  and other 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-thought.

Experience with  cloud infrastructure (AWS, GCP, Azure)  for scalable ML workflows.

Nice to Have

Experience with  agentic system design for LLM workflows .

Background in  conversational search .

Contributions to open-source projects in the retrieval, NLP, or LLM ecosystems.

Q:
What makes you thrive at Klue?
A:
We're looking for builders who:

Take ownership and run with…
Note that applications are not being accepted from your jurisdiction for this job currently via this jobsite. Candidate preferences are the decision of the Employer or Recruiting Agent, and are controlled by them alone.
To Search, View & Apply for jobs on this site that accept applications from your location or country, tap here to make a Search:
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)

Job Posting Language
Employment Category
Education (minimum level)
Filters
Education Level
Experience Level (years)
Posted in last:
Salary