Machine Learning Operations Engineer

7 days ago

Ottawa, Ontario, Canada Assent Compliance Inc. Full time
Job Description

We are seeking a highly skilled Machine Learning Operations Engineer to join our team at Assent Compliance Inc. in North America.

This role is responsible for developing and maintaining key machine learning infrastructure throughout its lifecycle. The Intermediate ML-Ops Engineer will ensure that ML and AI models deployed in production at Assent are performant, reliable, maintain (and improve in) accuracy over time, and integrate well with the overall Assent software suite.

The ideal candidate will have 2-4 years of experience in MLOps, machine learning engineering, or related fields, with hands-on experience deploying and maintaining ML models in production environments.

Key Responsibilities
  • Data Pipelines Development: Develop key data pipelines moving data into and out of ML and AI models in production environments for Assent's digital products;
  • ML-Ops Framework: Support the development of a robust ML-Ops framework to support model tracking and continuous improvement;
  • Statistical Analysis: Support ongoing and automated statistical analysis of ML models in production;
  • Performance Monitoring: Work closely with adjacent teams to proactively identify potential issues in performance and availability, with respect to data systems impacting ML models;

The successful candidate will be self-motivated and highly proactive at exploring new technologies and staying up to date with machine learning and AI principles, models, tools, and their applications in data processing and analysis.

Requirements and Qualifications
  • A degree in Computer Science, Engineering, or a related field (A Masters level degree, or higher, is highly preferred)
  • Demonstrable understanding of machine learning and AI principles, models, tools, and their applications in data processing and analysis
  • Strong knowledge of SQL for data retrieval
  • Excellent ability to use Python for data extraction and manipulation
  • Solid working knowledge of AWS systems and services; comfort working with SageMaker, EC2, S3, Lambda, Terraform
  • Solid working knowledge of MLOps, versioning, orchestration, and containerization tools; MLFlow, Kubeflow, Airflow, DVC, Weights & Biases, Docker, Kubernetes
What We Offer
  • A competitive base salary of $120,000 per year
  • A corporate bonus program
  • Comprehensive benefits packages
  • Vacation time that increases with tenure
  • Life leave days
  • Flexible work options
  • Volunteer days
  • Opportunities to get involved in corporate giving initiatives
  • Professional development days

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