Senior AI / Machine Learning Engineer

Revenue Roll; Canada; Remote; CAD 140,000 - 190,000; Full time

Job summary

Tie is seeking a Senior AI / ML Engineer to design, build, and deploy production ML systems at the heart of our identity graph and scoring platform. You’ll own models end to end—from feature engineering and training through deployment, monitoring, and iteration.

You will shape ML architecture, ship models with sub-second latency, and collaborate with platform engineering to ensure scalable AI systems. This is a hands-on, impact-driven senior role in a remote Canada-based team.

Qualifications

• 5+ years of experience building and deploying machine learning systems in production.
• Strong proficiency in Python for ML, data processing, and model serving.
• Hands-on experience with feature engineering, model training, and evaluation for real-world datasets.
• Experience deploying ML models via APIs or services (e.g., FastAPI, containers, Kubernetes).
• Solid understanding of data modeling, SQL, and analytical workflows.
• Experience working in a cloud environment (GCP, AWS, or equivalent).

Responsibilities

• Design and deploy production-grade ML models for identity resolution, propensity scoring, deliverability, and personalization.
• Build and maintain feature pipelines across batch and real-time systems (BigQuery, streaming events, graph-derived features).
• Develop and optimize classification models (e.g., XGBoost, logistic regression) with strong handling of class imbalance and noisy labels.
• Integrate ML models directly with graph databases to support real-time inference and identity scoring.
• Own model lifecycle concerns: evaluation, monitoring, drift detection, retraining, and performance reporting.
• Partner with engineering to expose models via low-latency APIs and scalable services.
• Contribute to GPU-accelerated and large-scale data processing efforts as we push graph computation from hours to minutes.
• Help shape ML best practices, tooling, and standards across the team.

Skills

Python for ML

Feature engineering

Model training

Model evaluation

Model deployment

SQL

Docker

Kubernetes

GCP

Neo4j

Cypher

Graph algorithms

XGBoost

Kafka

MLOps

CUDA

Spark

Tools

BigQuery

Python

Scikit-learn

XGBoost

Job description

Senior AI / Machine Learning Engineer

Location: Remote (Canada)

Engagement Type: B2B contractor

Team: Data Science & AI

Reports to: Head of Data Science & AI

About Tie

Tie is building the next generation of identity resolution and marketing intelligence. Our platform connects hundreds of millions of consumers across devices, browsers, and channels—without relying on cookies—to power higher deliverability, smarter targeting, and measurable revenue lift for modern marketing teams.

At Tie, AI is not a feature—it is a core execution advantage. We operate large-scale identity graphs, real-time scoring systems, and production ML pipelines that directly impact revenue, deliverability, and customer growth.

The Role

We are looking for a Senior AI / Machine Learning Engineer to design, build, and deploy production ML systems that sit at the heart of our identity graph and scoring platform. You will work at the intersection of machine learning, graph data, and real-time systems, owning models end to end—from feature engineering and training through deployment, monitoring, and iteration.

This role is highly hands-on and impact-driven. You will help define Tie’s ML architecture, ship models that operate at sub-second latency, and partner closely with platform engineering to ensure our AI systems scale reliably.

What You’ll Do

• Design and deploy production-grade ML models for identity resolution, propensity scoring, deliverability, and personalization
• Build and maintain feature pipelines across batch and real-time systems (BigQuery, streaming events, graph-derived features)
• Develop and optimize classification models (e.g., XGBoost, logistic regression) with strong handling of class imbalance and noisy labels
• Integrate ML models directly with graph databases to support real-time inference and identity scoring
• Own model lifecycle concerns: evaluation, monitoring, drift detection, retraining, and performance reporting
• Partner with engineering to expose models via low-latency APIs and scalable services
• Contribute to GPU-accelerated and large-scale data processing efforts as we push graph computation from hours to minutes
• Help shape ML best practices, tooling, and standards across the team

What You’ll Bring

Required Qualifications

• 5+ years of experience building and deploying machine learning systems in production
• Strong proficiency in Python for ML, data processing, and model serving
• Hands-on experience with feature engineering, model training, and evaluation for real-world datasets
• Experience deploying ML models via APIs or services (e.g., FastAPI, containers, Kubernetes)
• Solid understanding of data modeling, SQL, and analytical workflows
• Experience working in a cloud environment (GCP, AWS, or equivalent)

Preferred / Bonus Experience

• Experience with graph data, graph databases, or graph-based ML
• Familiarity with Neo4j, Cypher, or graph algorithms (community detection, entity resolution)
• Experience with XGBoost, tree-based models, or similar classical ML approaches
• Exposure to real-time or streaming systems (Kafka, Pub/Sub, event-driven architectures)
• Experience with MLOps tooling and practices (CI/CD for ML, monitoring, retraining pipelines)
• GPU or large-scale data processing experience (e.g., RAPIDS, CUDA, Spark, or similar)
• Domain experience in identity resolution, marketing technology, or email deliverability

Our Technology Stack

ML & Data: Python, Pandas, Scikit-learn, XGBoost

Graphs: Neo4j (Enterprise, GDS)

Cloud: Google Cloud Platform (BigQuery, Vertex AI, Cloud Run, Pub/Sub)

Infrastructure: Docker, Kubernetes, GitHub Actions

APIs: FastAPI, REST-based inference services

What We Offer

• Opportunity to work on core AI systems that directly impact revenue and product differentiation
• High ownership and autonomy in a senior, hands-on role
• Remote-first culture with a strong engineering and data focus
• Exposure to cutting-edge problems in identity resolution, graph ML, and real-time AI systems
• Clear growth path toward Staff / Principal IC roles

Why This Role Matters

At Tie, your work will not live in notebooks or experiments—it will power production systems used by real customers at scale. You will help define how AI is embedded into the company’s core platform and play a key role in making machine learning a durable competitive advantage.