Senior Machine Learning Engineer

Toronto, Ontario, Canada

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CA$175,000 – CA$210,000Compensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

SaaS, BiotechnologyIndustries

Requirements

The ideal candidate will have 5+ years of industry experience building and deploying ML systems, with at least 2 years focused on search, retrieval, or ranking systems. Expertise in Python and ML frameworks like PyTorch or TensorFlow is required, along with a deep understanding of information retrieval techniques (BM25, dense retrieval, hybrid retrieval) and relevance tuning. Experience with LLMs, RAG pipelines, prompt engineering, and designing production-grade ML systems at scale is essential. Familiarity with data pipelines, large-scale data handling, vector databases (FAISS, Milvus, etc.), traditional search engines (Elasticsearch, OpenSearch), and cloud ML infrastructure (AWS, GCP, Azure) is also necessary. Experience developing and implementing CI/CD pipelines for ML models and knowledge of query understanding and document summarization are expected.

Responsibilities

This role involves architecting, designing, and implementing retrieval pipelines and agentic workflows, including hybrid retrieval, re-ranking, and post-retrieval synthesis. You will lead the development of evaluation frameworks to measure and improve relevance, quality, and latency, and drive experimentation with query rewriting and expansion. Responsibilities include optimizing LLM workflows for low-latency, high-accuracy responses, collaborating cross-functionally with product and infrastructure teams, and mentoring junior team members. You will own data strategy for retrieval, design pipelines for insight extraction from diverse data sources, and evaluate and integrate advancements in LLMs and retrieval architectures into production systems. Additionally, you will automate the deployment and monitoring of ML models.

Skills

Machine Learning

LLM

Retrieval-Augmented Generation (RAG)

Dense Retrieval

Query Understanding

Agentic Reasoning

Search and Retrieval Systems

Architecture Design

Evaluation Frameworks

Re-ranking

Post-retrieval Synthesis

Query Rewriting

Query Expansion

Query Classification

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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