Lead AI/ML Engineer

Xsolla; Canada; On-site; CAD 90,000 - 120,000; Full time

Job summary

A global commerce company is seeking an experienced AI/ML Engineer to design and optimize algorithms in Vertex.ai. This role requires at least 5 years in the field, with strong skills in SQL and Python. Responsibilities include developing scalable data models and mentoring junior engineers. The ideal candidate will have experience with ETL/ELT processes and data pipeline orchestration. This position offers a collaborative environment with opportunities for growth and innovation.

Qualifications

• 5+ years of experience in AI/ML engineering.
• Strong SQL and Python skills.
• Deep understanding of algorithm performance tuning.
• Experience with data pipeline orchestration tools like Airflow or Prefect.

Responsibilities

• Design, build, and optimize algorithms in Vertex.ai.
• Develop scalable data models and lead integrations.
• Mentor junior AI/ML engineers.
• Collaborate with various teams to ensure compliance and governance.

Skills

AI/ML engineering

Vertex.ai

SQL

Python

ETL/ELT processes

Data pipeline orchestration

Kafka

GCP

Tools

Airflow

Looker

Tableau

Job description

Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game.

Responsibilities

• 1. Architecture & Development
• Design, build, and optimize algorithm in Vertex ai.
• Develop scalable data models, Algorithm supporting user 360 views, churn prediction, and recommendation engine inputs.
• Lead integration across data sources: MySQL, BigQuery, Redis, Kafka, GCP Storage, and API Gateway.
• Implement CI/CD for data pipelines using Git, dbt, and automated testing.
• Define data quality checks and auditing pipelines for ingestion and transformation layers.
• 2. Leadership & Collaboration
• Mentor and guide junior AI/ML engineers on data modeling, algorithm performance tuning.
• Partner with Data Science, ML, and Backend teams to productionize machine learning features in Snowflake.
• Work closely with Legal, Security, and Infrastructure teams to ensure compliance, privacy, and governance of user data (PII).
• Collaborate with the Director of Data Platforms and product stakeholders to translate business requirements into technical specifications.
• 3. Performance & Scalability
• Tune algorithm performance.
• Establish data partitioning, clustering, and materialized views for fast query execution.
• Build dashboards and monitors for pipeline health, job success, and data latency metrics (e.g., via Looker, Tableau, or Snowsight).
• 4. Governance & Best Practices
• Establish and enforce naming conventions, data lineage, and metadata standards across schemas.
• Lead code reviews, enforce documentation standards, and manage schema versioning.
• Contribute to the company’s evolving data mesh and streaming architecture vision.

Qualification & Skills

• 5+ years of experience in AI/ML engineering, with 3+ years in Vertex.ai.
• Strong SQL and Python skills, with proven experience building ETL/ELT at scale.
• Deep understanding of algorithm performance tuning, query optimization, and warehouse orchestration.
• Experience with data pipeline orchestration (Airflow, Prefect, dbt, or similar).
• Solid understanding of data modeling (Kimball, Data Vault, or hybrid).
• Proficiency in Kafka, GCP, or AWS for real-time or batch ingestion.
• Familiarity with API-based data integration and microservice architectures.
• Preferred
• Experience lead machine learning teams or/and deploying ML feature pipelines.
• Background in ad-tech, gaming, or e-commerce recommendation systems.
• Familiarity with data contracts and feature stores (Feast, Tecton, or custom-built).
• Experience managing small data engineering teams and setting technical direction
• Strong ownership and ability to work autonomously in a fast-paced environment.
• Excellent cross-functional communication — can translate between engineering and business.
• Hands-on problem solver who balances velocity with reliability.
• Collaborative mentor who raises the bar for team quality and discipline