Senior Real-Time AI Engineer — LLM & ML Platforms

Plusgrade; Montreal (administrative region); Hybrid; CAD 120,000 - 180,000; Full time

Benefits offered by this job

RRSP Matching

Comprehensive Health Plans

Flexible Paid Time Off

Travel Experience Perk

Annual Wellness Perk

Job summary

Plusgrade seeks a Senior Applied AI Developer to architect and productionize next-gen ML and LLM platforms for real-time, low-latency recommendation engines at scale. You will own the lifecycle of production models and build AI systems with AWS and Kubernetes.

The role requires deep expertise in ML tooling, software engineering, and scalable data pipelines, with a strong emphasis on reliability and observability across services.

Qualifications

• Proven track record of productionizing, scaling, and monitoring ML models and LLM recommendation systems in low-latency, highly available environments.
• Master software engineering with Python/Java and building robust RESTful APIs.
• End-to-end ML lifecycle ownership: data pipelines, CI/CD, MLOps, retraining, drift detection, quality governance.

Responsibilities

• Design, deploy, and scale low-latency ML/LLM recommendation pipelines feeding real-time predictive data.
• Own production models lifecycle from architecture to automated retraining and drift monitoring.
• Collaborate with Product, Operations, and Engineering to convert business challenges into AI solutions.

Skills

ML productionization

Low-latency systems

Python/Java

RESTful APIs

Docker & Kubernetes

AWS services

Tools

Python

Java

SQL

PySpark

AWS (EKS, SageMaker, Bedrock)

Kubernetes

Docker

Snowflake

GitLab

CI/CD

Argo CD

Job description

Plusgrade seeks a Senior Applied AI Developer to architect and productionize next-gen ML and LLM platforms for real-time, low-latency recommendation engines at scale. You will own the lifecycle of production models and build AI systems with AWS and Kubernetes.

The role requires deep expertise in ML tooling, software engineering, and scalable data pipelines, with a strong emphasis on reliability and observability across services.