Senior Machine Learning Engineer at Equinix — NeverHard
Senior Machine Learning Engineer at Equinix in Canada. Skills: Collaboration, Communication, Data Engineering, Data Modeling, Data Visualization. Apply on NeverHard.
Company
Equinix
Location
Canada
Type
full_time
Required skills:
Collaboration
Communication
Data Engineering
Data Modeling
Data Visualization
Generative AI
Hadoop
Kafka
MLOps
Machine Learning
The Senior Machine Learning Engineer designs and implements advanced ML solutions leveraging Generative AI and Predictive AI to solve complex business challenges.
This role partners with cross-functional teams to build scalable models, extract insights from design documents, and deliver automation that drives measurable impact. The Senior MLE combines strong technical expertise with practical business understanding to accelerate AI adoption across the enterprise
AI & ML Development
Build and deploy ML models using GenAI and Predictive AI for forecasting, optimization, and intelligent automation
Apply NLP and document analysis techniques to extract actionable insights from design documents
Solution Architecture
Design robust ML pipelines and architectures for enterprise-scale applications
Ensure solutions align with organizational goals and technology standards
Data Engineering & Modeling
Develop efficient data models and wrangling strategies for large, complex datasets
Drive data discovery initiatives and communicate patterns and hypotheses to stakeholders
Software Engineering
Implement ML frameworks and coding best practices using Python, TensorFlow/PyTorch
Integrate solutions with Big Data technologies (Spark, Kafka, Hadoop) for real-time and batch processing
Visualization & Insights
Create dashboards and visualizations to present ML-driven insights in a business-friendly format
Translate model outputs into actionable recommendations for decision-makers
Testing & Quality
Develop repeatable test strategies for ML models ensuring accuracy and reliability
Certify releases for performance and customer experience
Collaboration & Stakeholder Engagement
Work closely with product managers, data engineers, and business teams to identify high-value AI use cases
Communicate technical concepts clearly to non-technical stakeholders