Senior ML Engineer

Overview:

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
• Experience fine‑tuning LLMs and embedding models

What We Offer:

• Paid Time Off
• Comprehensive benefits plan
• Company RRSP Match
• Development opportunities through the LinkedIn Learning platform

About Guidepoint:

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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