Engineering Manager, Data Science – AdTech

This is a fully remote position, open to applicants in Canada.

📋 Description

• Lead the transformation of Deep Learning: Manage the transition from traditional tree-based models (XGBoost) to cutting-edge Neural Network architectures for audience propensity, lookalike modeling, and real-time segmentation.

• Take ownership of Value-Based Bidding (ROAS): Advance our bidding strategy from basic conversion predictions to complex ROAS-focused optimization, creating models that forecast user value (LTV) to enhance client returns in dynamic auction scenarios.

• Advocate for Agentic AI & Automation: Drive the investigation and implementation of autonomous workflows to improve decision-making and operational effectiveness, evolving from static models to self-adjusting systems.

• Develop Production Deep Learning Systems: Supervise the comprehensive engineering of large-scale inference pipelines, which include embedding layers, real-time feature stores, and low-latency serving infrastructure such as ONNX and TensorRT.

• Promote MLOps & Experimentation: Implement stringent MLOps protocols for model version control and drift detection while advancing towards multi-armed bandit methodologies (Exploration vs. Exploitation) that prioritize business outcomes (Revenue/GP) over mere model metrics.

• Direct and expand the Data Science team: Responsible for hiring, mentoring, performance management, and career development.

• Collaborate with Product and Client Success teams to translate business needs into machine learning solutions and effectively communicate model capabilities.

• Work with the Data Platform team to guarantee dependable data foundations and feature pipelines for modeling.

• Convert intricate ML concepts into actionable insights for business stakeholders and executives.

• Establish the technical vision and cultivate a culture of innovation, rigor, and continuous enhancement.

⛳️ Requirements

• PhD (preferred) or Master’s Degree in Computer Science, Mathematics, or a related Quantitative Field.

• Over 8 years of experience in Data Science or ML Engineering, including at least 2 years in a managerial or leadership role.

• Expertise in AdTech Deep Learning Architecture: Extensive hands-on experience with contemporary ranking and retrieval architectures (e.g., DLRM, DCNv2, Two-Tower), emphasizing multi-objective learning (MMoE) to optimize clicks, conversions, and revenue concurrently.

• Strategic Leadership in Agentic AI: Proven enthusiasm and skill in shaping the roadmap for autonomous agentic systems. Must be eager to learn, advocate for, and take ownership of the transition from static RAG to production-quality agentic orchestration.

• Real-Time Inference & Engineering: Experience in deploying complex models within high-throughput, low-latency production settings (familiarity with ONNX, TensorRT, or feature stores).

• Business & Commercial Acumen: Ability to convert enhanced model performance (AUC/LogLoss) into actionable business metrics (GP, RPM) and prioritize R&D initiatives based on ROI and unit economics.

• Strong proficiency in Python, with a focus on Deep Learning frameworks (PyTorch, TensorFlow) as well as traditional ML libraries (XGBoost, scikit-learn).

• Proven leadership abilities: Experience in hiring, mentoring, and nurturing high-performing data science talent.

• Exceptional communication skills to convey technical concepts to business stakeholders and executives.

🏝️ Benefits

• Competitive compensation

• Ample career and professional growth opportunities

• New Headquarters with an open floor plan to foster collaboration

• Health, dental, and vision insurance

• Pre-tax savings plans and transit/parking programs

• 401K with competitive employer match

• Volunteer and philanthropic activities throughout the year

• Educational and social events

• An incredible opportunity to work for a leading performance marketing company!