Backend Engineer, AI / ML

Klue; Vancouver, Toronto; On-site; CAD 145,000 - 180,000; Full time

Job summary

A tech company in Vancouver is seeking a Backend Engineer with a focus on AI/ML. You will design and build retrieval infrastructure, optimizing it for real-time user-facing systems. The ideal candidate will have strong backend programming skills and experience in search and retrieval systems. Competitive salary range is CA$145,000 - CA$180,000, with hybrid working options.

Benefits

Extended health & dental benefits

Employee Stock Option Plan

Flexible PTO policy

Qualifications

• 3+ years of backend engineering experience, ideally in search and retrieval systems.
• Strong programming skills in Python, Ruby, or similar backend languages.
• Experience with search infrastructure and vector search systems.

Responsibilities

• Design, implement, and maintain retrieval infrastructure and APIs.
• Integrate dense retrieval and hybrid retrieval models into live systems.
• Optimize latency and throughput of retrieval systems.

Skills

Backend engineering experience

Strong programming skills in Python or Ruby

Experience with search infrastructure

Understanding of retrieval pipelines

Familiarity with real-time data pipelines

Experience with distributed systems

Familiarity with cloud infrastructure

Strong debugging and profiling skills

Tools

Elasticsearch

Docker

Kubernetes

GCP

Kafka

Job description

Overview

Klue is hiring a Backend Engineer, AI / ML to join our team in Toronto to work on LLM-powered search and retrieval agents. In this role, you will build and optimize the retrieval infrastructure, APIs, and data pipelines that power our ML team’s agentic workflows, enabling fast, accurate, and scalable retrieval for advanced user-facing systems.

What you’ll do on a day to day basis

• Design, implement, and maintain retrieval infrastructure and APIs that interface seamlessly with LLM-based agent workflows.
• Integrate dense retrieval, hybrid retrieval, and re-ranking models into live systems.
• Optimize latency, scalability, and throughput of retrieval systems for real-time agentic pipelines.
• Build and maintain vector database infrastructure (FAISS, Milvus, Weaviate, Pinecone, PGVector) and traditional search engines (Elasticsearch, OpenSearch).
• Support retrieval-augmented generation (RAG) workflows, including efficient query execution, chunk retrieval, and caching strategies.
• Develop monitoring and observability tools for retrieval pipelines to ensure reliability and transparency.
• Work with ML engineers on data pipelines for indexing and re-indexing, enabling continuous improvement of search relevance.
• Contribute to the architecture of multi-step retrieval agents, ensuring clean abstractions between the backend and ML layers.

What experience we’re looking for

• 3+ years of backend engineering experience, ideally in search, retrieval systems, or high-scale APIs.
• Strong programming skills in Python, Ruby, or similar backend languages.
• Experience with search infrastructure (Elasticsearch, OpenSearch, Vespa) and vector search systems.
• Understanding of retrieval pipelines, dense retrieval, and hybrid search.
• Familiarity with real-time data pipelines (Kafka, Pub / Sub) for indexing workflows.
• Experience with distributed systems and microservices, with a focus on reliability and performance.
• Familiarity with cloud infrastructure (AWS, GCP, Azure) and container orchestration (Kubernetes).
• Ability to work collaboratively with ML Engineers, understanding their experimentation workflows and constraints.
• Strong debugging and profiling skills for production systems.

Nice to Have

• Experience with retrieval-augmented generation (RAG) or agentic retrieval workflows.
• Exposure to prompt engineering and LLM system integration.
• Contributions to open-source projects in search or retrieval.

What makes you thrive at Klue?

• 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

Technologies 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

Working style

• Hybrid. Best of both worlds (remote & in-office). You and your team will be in the office 2 days a week.
• Our main Canadian hubs are in Vancouver and Toronto, and most of our teams are located in EST and PST.

Compensation & Benefits

• Pay range: CA$145,000 - CA$180,000 per year
• 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. The average Klue team member takes 2-4 weeks of PTO per year, with approval from your team in advance
• Direct access to our leadership team, including our CEO

Equal Opportunity

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.