Guidepoint seeks an experienced Senior AI/ML Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products.
This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products.
Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services.
This is a hybrid position based in Toronto.
What You'll Do:
Develop LLM-powered solutions such as retrieval-augmented generation (RAG) pipelines, agentic research assistants, and content synthesis tools using proprietary knowledge repositories
Build, scale, and optimize GenAI and ML workloads across Databricks and other production environments, with strong attention to cost-efficiency, compliance, and robustness
Implement AI agents capable of performing research, answering complex queries, or augmenting client interactions using structured and unstructured data
Build ML pipelines to train, serve, and monitor reinforcement learning or supervised learning models using Databricks and MLFlow
Explore fine-tuning, few-shot, and prompt-engineering strategies to customize open-source and proprietary LLMs
Collaborate with data engineering and data science teams to define best practices for LLMOps, AI observability, and continuous evaluation of model performance
Contribute to the architecture of intelligent systems that combine GenAI with real-time data, APIs, and domain-specific tools
Collaborate with product and client services teams to define priorities and influence the product roadmap
Mentor junior AI/ML engineers and help build a responsible, scalable AI infrastructure across the organization
What You Have:
6+ years of related experience with a Bachelor’s degree; or 3+ years and a Master’s degree; or a PhD with 1 year experience
Proven experience designing and deploying applications using Generative AI and large language models (e.g., GPT-4, Claude, open-weight LLMs)
Experience with retrieval-augmented generation, embeddings-based search, agent orchestration, or prompt chaining
Familiarity with modern LLM/GenAI tools such as Langchain, LlamaIndex, HuggingFace Transformers, Semantic Kernel, or LangGraph
- Strong technical proficiency in Python, FastAPI, Kubernetes, Azure Cloud platform, and Elasticsearch for vector search and hybrid information retrieval systems
5+ years of hands-on industry experience in data science, machine learning, or AI application development
Proficient in core ML libraries such as pandas, scikit-learn, PyTorch, and TensorFlow
Demonstrated leadership ability in building and scaling AI/ML systems
Excellent communication and collaboration skills across engineering, product, and business stakeholders
Experience designing GenAI systems that support end-user applications such as research assistants, content summarizers, or copilots
Knowledge of evaluation and monitoring techniques for LLM-based applications, including human-in-the-loop review and rubric-based scoring
Familiarity with Delta Lake and Unity Catalog
Experience working with Apache Spark to process large, distributed datasets
Background in customer behavior modeling, propensity scoring, or personalization techniques
Understanding of building compliant and explainable AI solutions in regulated industries
You will also be eligible for the following benefits:
Paid Time Off
Comprehensive benefits plan
Company RRSP Match
Development opportunities through the LinkedIn Learning platform
Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients’ decision-making process. Powered by innovative technology, real-time data, and hard-to-source expertise, we help our clients to turn answers into action.
Backed by a network of nearly 1.5 million experts, and Guidepoint’s 1,300 employees worldwide, we inform leading organizations’ research by delivering on-demand intelligence and research on request. With Guidepoint, companies and investors can better navigate the abundance of information available today, making it both more useful and more powerful.
At Guidepoint, our success relies on the diversity of our employees, advisors, and client base, which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community, regardless of background, identity, or experience.
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