AI/ML Engineer at Guidepoint

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

23 Dec, 25

Salary

0.0

Posted On

24 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Evaluation Frameworks, Generative AI, Large Language Models, Machine Learning, Databricks, Python, Azure, FastAPI, Kubernetes, NLP, Data Processing, Model Monitoring, Responsible AI, Prompt Engineering, Agent Orchestration, Fine-Tuning

Industry

Information Services

Description

Overview: Guidepoint seeks an experienced AI/ML Engineer as an integral member of the Toronto-based Data 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 role requires strong technical expertise and leadership to design, implement, and scale intelligent systems that leverage large language models (LLMs), advanced ML pipelines and Building Agents in Databricks. You will drive the development of AI evaluation frameworks, scalable deployment practices, and robust monitoring systems to ensure quality, reliability, and responsible AI outcomes. The AI/ML Engineer will play a key role in expanding Guidepoint’s AI/ML capabilities using Databricks and other modern cloud-native tools. This is a hybrid position based in Toronto. What You’ll Do: Design and implement LLM-powered solutions such as retrieval-augmented generation (RAG) pipelines, Build, scale, and optimize GenAI and ML workloads across Databricks and other production environments, focusing on cost-efficiency, compliance, and reliability Develop robust AI evaluation frameworks and monitoring systems for continuous model assessment, including rubric-based scoring and human-in-the-loop validation Implement AI agents capable of handling complex queries and delivering insights from structured and unstructured data sources Build ML pipelines to train, serve, and monitor supervised, reinforcement, and LLM-based models using Databricks and MLflow Explore strategies such as fine-tuning, few-shot learning, and prompt engineering to adapt open-source and proprietary LLMs Collaborate with data engineering and data science teams to establish best practices for LLMOps, observability, and responsible AI integration Contribute to the architecture of intelligent systems that combine GenAI with real-time data, APIs, and domain-specific tools Partner with product and client services teams to define priorities and align AI capabilities with business outcomes What You Have: 4+ years of related experience with a Bachelor’s degree; or 3+ years with a Master’s degree; or 1+ year with a PhD Proven experience designing and deploying Generative AI/LLM applications (e.g., ASR Models,GPT-4, Gemini, Claude, open-weight models) Hands-on expertise with Gen AI Pipelines, retrieval-augmented generation, embeddings-based search, agent orchestration, and prompt chaining Familiarity with modern LLM/GenAI frameworks (Mosaic AI, LangChain, LlamaIndex, HuggingFace, Semantic Kernel, LangGraph) Strong technical proficiency in Python, Databricks, Azure, FastAPI, Kubernetes, 4+ years of hands-on industry experience in AI application development Proven ability to design AI evaluation pipelines. LLMOps, monitoring frameworks for production-grade LLM/ML systems Demonstrated leadership in building and scaling applied AI/ML systems for real-world use cases Excellent collaboration and communication skills across engineering, product, and business teams Familiarity with Delta Lake, Unity Catalog, and large-scale data processing with Apache Spark Knowledge of personalization techniques, NLP-based modeling, and applied ML for user experience optimization Experience with fine-tuning LLMs and embedding models for domain-specific tasks Understanding of responsible AI practices, including explainability, compliance, and bias mitigation 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 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 1.75 million experts, and Guidepoint’s 1,600 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. #LI-DH1 #LI-Hybrid

Responsibilities

Design and implement LLM-powered solutions and build, scale, and optimize GenAI and ML workloads. Collaborate with data engineering and data science teams to establish best practices for LLMOps and responsible AI integration.