Senior ML Engineer: Build Real-World AI Platform

Wiser; Canada; Remote; CAD 160,000 - 200,000; Full time

Benefits offered by this job

Remote work

Job summary

Wiser Solutions is hiring a Senior ML Engineer to build our customer-facing AI platform and deliver first features to customers. You will own ML systems from idea to prototype to production, focusing on practical, cost-aware solutions across matching, classification, and attribute extraction.

The role involves deployed ML workflows, RAG systems, embeddings, and LLM-powered features on AWS, with an emphasis on moving fast and delivering working prototypes over slides.

Qualifications

• 7+ years in ML engineering, applied data science, or AI engineering.
• Track record of shipping ML/AI systems to production and owning them after launch.
• Hands-on experience training and evaluating models: feature engineering, experiment design, metrics.
• Hands-on experience building production apps with LLMs, including RAG and embeddings.

Responsibilities

• Take customer problems from idea to prototype quickly and move successful approaches to production.
• Train, fine-tune, and evaluate models for matching, classification, and extraction.
• Design and ship RAG systems, embedding-based retrieval, and LLM-powered features on AWS.
• Own the full ML lifecycle: experiment tracking, versioning, deployment, monitoring, retraining.
• Build evaluation sets and metrics, including offline metrics and LLM-judge use cases.
• Monitor production models for drift, latency, and cost per prediction.

Skills

Python

Experimentation

CI/CD

Testing

Code review

AI tooling

AI coding assistants

Tools

MLflow

SageMaker Pipelines

Weights & Biases

Airflow

SageMaker

Bedrock

Lambda

ECS/EKS

S3

Job description

Wiser Solutions is hiring a Senior ML Engineer to build our customer-facing AI platform and deliver first features to customers. You will own ML systems from idea to prototype to production, focusing on practical, cost-aware solutions across matching, classification, and attribute extraction.

The role involves deployed ML workflows, RAG systems, embeddings, and LLM-powered features on AWS, with an emphasis on moving fast and delivering working prototypes over slides.