Klue

Software Engineer II, AI

Klue$90K — $120K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of software engineering experience
  • Proven background in information retrieval systems and ranking models
  • Strong proficiency in Python; experience with PyTorch, TensorFlow, or JAX
  • Familiarity with LLMs and retrieval-augmented generation concepts
  • Knowledge of query understanding and document summarization techniques
  • Experience with vector databases and traditional search engines
  • Capable of working independently and collaboratively in a dynamic environment.

Responsibilities

  • Design and implement retrieval-augmented generation systems with advanced workflows
  • Build and optimize retrieval pipelines using various approaches
  • Develop pipelines for evaluating retrieval and generation performance
  • Initiate experiments for refining query strategies and relevance
  • Collaborate with Product to launch ML-powered search agents
  • Profile and optimize system components for performance and scalability
  • Contribute to the design and management of data pipelines for model training.

Benefits

  • Extended health and dental coverage from Day 1
  • Employee Stock Option Plan participation for all full-time employees
  • Take The Time You Need vacation policy with flexibility
  • High-performance culture with growth and development opportunities
  • Access to top-tier tools, including a Mac or PC of your choice
  • AI-first environment encouraging innovation and creative showcases
  • Social and team-building events throughout the year.
Full Job Description
We're looking for a Software Engineer, AI 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. 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. What You'll Do - 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. What You Bring - 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. - Background in conversational search. - Contributions to open-source projects in the retrieval, NLP, or LLM ecosystems. What Success Looks Like 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 Our Tech Stack - 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 We encourage candidates to apply to the engineering role and level that best align with their experience. To support a fair and consistent review process, candidates are limited to one engineering application every 60 days. Applying to multiple roles will not improve consideration, as our team evaluates candidates holistically across our engineering career framework throughout the interview process. ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ ↓ 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. How We Work at Klue We love the balance of connection and flexibility. We work Office-First, with ahybrid touch, and work together in our vibrant offices on Mondays, Wednesdays & Thursdays to collaborate, brainstorm, and build together. Our main hiring hubs are in: - C🇦 Vancouver (HQ) - C🇦 Toronto - GB London Our Commitment to You - High Performance Culture. We reward high performance and growth through career development, coaching, and annual performance reviews. - Comprehensive benefits: Extended health & dental coverage that starts on Day 1. Fun perks like discounts at Goodlife and Perkopolis are gravy. - Ownership: All full-time employees have the opportunity to participate in our Employee Stock Option Plan. - Our Vacation Policy is Take The Time You Need. We just ask that you give notice and don't leave your team hanging. - Top-tier tools. All employees will receive a Mac (or PC, if that's your jam) and access to A+ tooling. - AI First. All employees are encouraged to lean into AI to work smarter and faster. Built something cool lately? Show us at our Friday Show, Don't Tell Meetings. - Growth / Leadership. Direct access to our leadership team, including our CEO, and opportunities to connect with incredible people across the company. - Social connection. There's no shortage of ways to stay connected and have fun. We get together once a year in Vancouver for a company- wide kickoff. Throughout the year our Hubs hold regular social events. - Dog-friendly spaces. Bring your four-legged friend along in Vancouver or Toronto, as our offices are pup-approved.

About Klue

Klue is a competitive enablement platform designed to help companies collect, curate, and distribute competitive intelligence. The platform enables sales teams to collect and curate competitive intelligence and then distribute it to the rest of the organization. Klue's platform integrates with Salesforce, Slack, and other tools to provide a seamless experience for users. The company was founded in 2015 and is headquartered in Vancouver, Canada.
Learn more about Klue
Size
50 employees
Industry
Founded
2015

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