Machine Learning Engineer, AI/ML at Klue

Toronto, Ontario, Canada

Klue Logo
CA$155,000 – CA$180,000Compensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
SaaS, Technology, AIIndustries

Requirements

  • 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, TensorFlow, 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, OpenSearch)
  • 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

Responsibilities

  • 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

Skills

Key technologies and capabilities for this role

RAGLLMBM25dense retrievalhybrid retrievalre-rankingretrieval pipelinesagentic workflowsevaluation frameworksBackendMachine Learning

Questions & Answers

Common questions about this position

What is the salary range for this Machine Learning Engineer position?

The salary range is CA$155K - CA$180K.

Is this role remote or hybrid, and where is it located?

The position is hybrid and based in Toronto.

What skills and experience are required for this role?

Candidates need 5+ years of software engineering experience, expertise in information retrieval systems, search relevance, and ranking models, and proficiency in Python with frameworks like PyTorch, TensorFlow, or JAX, plus familiarity with LLMs and prompt engineering.

What is the company culture like at Klue?

Klue has an experienced leadership team working alongside several hundred risk-taking builders, and is recognized as one of Canada’s Most Admired Corporate Cultures, a Deloitte Technology Fast 50 & Fast 500 winner, and recipient of Startup of the Year and Tech Culture of the Year awards.

What makes a strong candidate for this Machine Learning Engineer role?

A strong candidate has strong Backend and ML fundamentals, 5+ years of software engineering experience, and expertise in information retrieval, Python ML frameworks, and LLMs, with a passion for practical LLM applications.

Klue

AI-driven competitive intelligence platform

About Klue

Klue provides a competitive intelligence platform that helps businesses understand their market, competitors, and buyers. The platform uses artificial intelligence to gather data from millions of sources and highlights the most relevant insights for its users. This information is centralized, making it easy for teams to access and utilize. Klue offers features like battlecards and newsletters that deliver real-time intelligence to sales representatives, enhancing their ability to compete effectively. Unlike many competitors, Klue focuses on delivering a comprehensive view of the competitive landscape, which allows businesses to make informed strategic decisions. The goal of Klue is to enable its clients to improve their win rates and measure the impact of competitive intelligence on their revenue, ultimately providing a clear return on investment.

Vancouver, CanadaHeadquarters
2015Year Founded
$87MTotal Funding
GRANTCompany Stage
Data & Analytics, Enterprise Software, AI & Machine LearningIndustries
201-500Employees

Benefits

Competitive base compensation
Extended health & dental benefits
Unlimited vacation
Employee Stock Option Plan
Pension fund
Yearly fully-paid trips to Vancouver headquarters
Free access to an online learning tool offering many engineering courses

Risks

Emerging AI-driven platforms could erode Klue's market share.
Rapid AI advancements may lead to technological obsolescence for Klue.
Customer privacy concerns could limit Klue's data collection capabilities.

Differentiation

Klue uses AI to provide actionable competitive intelligence insights efficiently.
The platform integrates with Salesforce for consistent and reliable data insights.
Klue's AI-Generated Strengths and Weaknesses feature reduces manual analysis time significantly.

Upsides

Klue's rapid growth is validated by its inclusion in Deloitte's Fast 50 and 500 lists.
The launch of Klue Win-Loss aids unbiased decision-making in product and market strategies.
Generative AI and LLMs enhance the depth and accuracy of Klue's insights.

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