Software Engineer (AI Platform)
Location : Vancouver, BC, Canada – Hybrid – Permanent
Salary : CA$140,000.00 / yr – CA$150,000.00 / yr
Responsibilities
- Contribute to the design and development of core AI platform components to support machine learning lifecycle workflows (data and metadata ingestion, storage and indexing, model training, validation, deployment) within a live-service gaming environment
- Implement and maintain cloud-based infrastructure (on AWS, GCP or Azure) supporting scalable ML workloads, ensuring reliability, availability and cost‑efficiency for game operations
- Assist in automating end-to-end AI workflows : build CI / CD pipelines for model deployment, containerized micro‑services (Docker / Kubernetes), and metric instrumentation for model performance and monitoring
- Work alongside data scientists, ML engineers and game developers to integrate ML models into production systems, support deployment, conduct testing and troubleshoot performance or reliability issues in live environments
- Develop and maintain scripts, services or platform modules for feature pipelines, model orchestration, data‑lake or lakehouse interactions (e.g., Spark, Redshift, Snowflake)
- Monitor, tune and optimise model performance, scalability, and cost‑efficiency in production, contributing suggestions and implementation of improvements under the direction of senior engineers
Must-Haves
Master’s degree or equivalent in Computer Science, AI, ML, or related field, or Bachelor degree or equivalent in Computer Science, Electrical Engineering, or related field with 3+ years of software engineering experience with a focus on AI / ML systems or platform developmentFamiliarity with deep‑learning frameworks (e.g., PyTorch) and a basic understanding of machine learning lifecycle : model development, evaluation, deploymentProficiency in Python programmingExperience working with containerization (Docker), orchestration (Kubernetes) and CI / CD pipelines in a cloud environmentExperience with data‑lake or lakehouse technologies (e.g., Spark, Redshift, Snowflake, Trino)Understanding of deploying and monitoring ML models in production, including performance, scalability, reliability, and cost considerationsStrong problem‑solving and collaboration skills, attention to detail, and excellent communication written and verbalPlusses
Exposure to cloud platforms (AWS, GCP, or Azure) and infrastructure‑as‑code tooling (e.g., Terraform, CloudFormation) is highly desirableExposure to generative AI technologies (e.g., diffusion models, large language models), experience in a live service or gaming environment, or prior project work in end‑to‑end ML systemsExperience with one or more additional languages (e.g., Java, Go, C++)Seniority Level
Mid‑Senior level
Employment Type
Full-time
Job Function
Information Technology
Industries
Entertainment Providers
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