ML Engineer: Production Models & Pipelines (AWS)

Geo Logic Systems Corp; Calgary; On-site; CAD 115,000 - 130,000; Full time

Job summary

Geo Logic Systems Corp in Calgary, Alberta is seeking an ML Developer to build, optimize, and deploy machine learning models and data pipelines within an AWS environment, applying software development best practices.

You will work across the ML lifecycle from experiments to production and drift detection, collaborating with data scientists, architects, and product teams, with minimal supervision.

Qualifications

• Minimum 4 years delivering AI/ML projects end to end.
• Hands-on experience building AI/ML solutions in AWS.
• Proficiency in Python with at least one other language.
• Solid software engineering fundamentals including TDD and CI/CD.
• Knowledge of relational and non-relational databases and SQL.

Responsibilities

• Participate in team planning sessions and contribute to effort estimation for ML and software development work.
• Build, optimize, and maintain ML models and data pipelines from prototype through to production.
• Apply software development best practices, including test-driven development and CI/CD, to all model and pipeline work.
• Design and implement operational aspects of model deployment, covering automation, monitoring, and drift detection.
• Collaborate with architects, data scientists, and product and business teams to develop and refine ML solutions.
• Review requirements, participate in experiments, and prototype solutions that address business needs.
• Perform code reviews and provide constructive, actionable feedback to peers.
• Test and debug application code to ensure reliability and performance.

Skills

Python

Java

C#

AWS

SQL

DevOps

ML algorithms

Testing

Education

BSc/MSc in CS/Engineering/Math/Physics/Statistics

Tools

Databricks

Job description

Geo Logic Systems Corp in Calgary, Alberta is seeking an ML Developer to build, optimize, and deploy machine learning models and data pipelines within an AWS environment, applying software development best practices.

You will work across the ML lifecycle from experiments to production and drift detection, collaborating with data scientists, architects, and product teams, with minimal supervision.