Machine Learning Engineer

About Point11 and Our Mission

We are creating the essential infrastructure for the emerging agent-driven era. Just as mobile adoption redefined brand success a decade ago, the way people interact with businesses is shifting from static webpages to dynamic conversations. Currently, 800 million people discover brands via agent search, and the decision of which brand is chosen happens in real time.

Team Overview

At Point11, we develop digital twins that accurately represent customers. You will manage the models and data, including the construction of twins from company records, evaluating their behavioral fidelity compared to real customers, and enhancing their performance with each campaign. Every interaction must be intelligent and respond within 0.11 seconds. Our team is small but held to high standards, founded by former Google employees.

Initial Year Responsibilities

• Evaluate how well digital twins predict actual customer behavior and reduce discrepancies.
• Create forecasting models that translate campaign results into actionable demand predictions for brands.
• Develop training and assessment pipelines that improve customer-specific twins without compromising data privacy across companies.

Typical Daily Tasks

• Lead modeling efforts for digital twins, covering feature engineering, model training, evaluation, and deployment.
• Develop data pipelines to transform customer CRM and data warehouse information into formats suitable for modeling.
• Conduct experiments with clear hypotheses and produce objective, honest outcomes.
• Collaborate with AI Engineers to delineate the role of models versus large language model-based agents.
• Deploy models into production and maintain high standards of model quality post-deployment.

Candidate Profile

• Proven experience in developing and deploying machine learning models that operate in production environments.
• Strong proficiency in Python and modern machine learning toolsets.
• Committed to rigorous evaluation practices, establishing baselines, and ensuring statistical soundness.
• Able to communicate model assumptions and behavior effectively to both engineering teams and customers.
• Based in Toronto or willing to relocate; position requires hybrid work with three days onsite weekly at our Toronto office.

Preferred Additional Skills

• Experience with forecasting, causal inference, or recommendation systems.
• Knowledge of synthetic data generation or simulation techniques.
• Expertise in privacy-preserving or multi-tenant machine learning frameworks.
• Familiarity with fine-tuning large language models or working with embeddings.

What We Offer

• Critical role influencing the accuracy and reliability of our product's digital twins.
• Hybrid working arrangement located in Toronto, aligned with New York time zone hours.
• Opportunity to be among the founding members of Point11’s Canadian team.
• Direct access to the founding team for product discussions and insights.
• Annual budget allocated for professional development, including conferences and training.

Equal Opportunity Employment

Point11 is committed to providing equal employment opportunities to all current and prospective employees without discrimination based on race, color, religion, sex, gender identity, national origin, sexual orientation, age, pregnancy, disability, marital status, or any other legally protected status in the country of employment.