ThoughtExchange

Role Description We are looking for a Senior Applied Machine Learning Scientist with a mission of building and owning the ML systems that power ThoughtExchange’s AI capabilities. In this role, you’ll take end-to-end ownership of complex machine learning projects from research and experimentation through to production that directly shape how our platform delivers insights to leaders across North America. As the foundational ML scientist on the team, your technical decisions will have an outsized impact on our product and the communities we serve. If you thrive in exploratory problem-solving, care deeply about technical quality, and want to see your work make a real difference, we’d love to hear from you. What You’ll Do - Leads and is accountable for the full machine learning lifecycle from research and experimentation through to production, applying scientific methodology and sound technical trade-offs to deliver robust, scalable solutions. - Build and own the AI quality platform, including evaluation frameworks, monitoring, and guardrails, enabling engineers across the organization to safely iterate on prompts and models. - Research emerging ML technologies and methodologies, and drive adoption decisions for the team’s tools and processes. - Leads open-ended analytical investigations, translating ambiguous business questions into structured approaches and actionable findings. - Leads the design of scalable, maintainable ML solutions, proactively managing technical debt and anticipating future needs. - Write clean, testable, and well-documented code for customer-facing features, data pipelines, and experimentation, and debug complex issues across product areas to resolve root causes. - Collaborate with Engineering, Product, and Design teams to elevate the team’s technical practices and influence priorities. Qualifications - 5+ years of professional experience in machine learning, data science, or software engineering with applied ML responsibility. - Strong programming skills in Python, with experience using common machine learning libraries and frameworks. - Deep understanding of machine learning fundamentals, statistical modeling, evaluation techniques, and system design principles. - Hands-on experience deploying and supporting machine learning models in production environments. - Experience working with relational databases (e.g., PostgreSQL) and large datasets. - Experience building or working with LLM evaluation and observability tooling (e.g., evals frameworks, prompt versioning, model comparison pipelines). - Comfortable operating in both exploratory, ambiguous analytical contexts and structured production delivery. - Strong collaboration skills with the ability to explain complex technical concepts to non-technical colleagues. Nice to Have - Master’s or PhD in Machine Learning, Data Science, or a related field. - Familiarity with cloud-based systems and services, preferably AWS. - Familiarity with software engineering best practices including version control, testing, and CI/CD. Salary Range The hiring range for this role is $141,848–157,609 CAD. Your specific compensation within this range is determined based on your job-related skills, knowledge, experience, and our internal equity assessment. Benefits - From day one, you’ll receive a benefits package focused on health & wellness that includes a generous time off policy, flexible extended benefits plan options, and company-wide wellness days off scheduled throughout the year. - Our benefits package also includes maternity & parental leave top-up programs, as well as access to Maple & Inklbot, which support our employees' primary care, mental health, and wellness needs. - We’ve been remote-first for over ten years. We’re contribution-focused and operate on mutual trust because we need you to feel empowered to be your best self. - We walk the walk when it comes to our product, ensuring that no critical decisions are made without including our employees' perspectives. - We want you to do your best work, and part of that is being happy with your compensation. We pay fairly, considering the complexities of market rates, experience, location, and demand. - In addition to competitive pay and benefits, employees receive share options when joining the company. - We host regular learning sessions. You also have access to an annual Professional Development stipend & Company Coach to ensure you can grow in your role & advance your career.