Senior Machine Learning Engineer

Just Eat Takeaway.com•Canada, AB Remote, AB

About The Position

As a Senior ML Engineer, you will take a leadership role in shaping the strategic direction of our machine learning infrastructure, proactively identifying opportunities for innovation and improvement. You will drive the development of cutting-edge solutions that enhance the performance, scalability, and reliability of our machine learning systems. In collaboration with the Data Science team, you will ensure that models are deployed seamlessly, optimized for production environments, and meet the highest standards of efficiency and accuracy at scale. You will also be responsible for architecting and overseeing the development of complex machine learning pipelines, managing both real-time and batch inference systems that are integral to our predictive platforms. You will work closely with cross-functional teams to anticipate future needs, recommending and implementing long-term solutions that align with our business objectives. As a senior member of the team, you will mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organization. Your expertise will play a key role in conducting comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration. Beyond technical execution, you will be expected to communicate effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights. You will present innovative solutions to key stakeholders, making compelling cases for new initiatives and guiding the strategic direction of our machine learning efforts. Finally, you will lead the integration of new technologies and tools into our infrastructure, staying ahead of industry trends and ensuring that our machine learning frameworks remain at the cutting edge of technological advancements.

Requirements

Expert-level proficiency with cloud technologies (ideally AWS)
Extensive experience with containerization and orchestration (preferably Kubernetes)
Deep understanding of software development, DevOps, and MLOps best practices, with a proven track record of applying them in production
Extensive experience in designing, deploying, and maintaining scalable models and services in production environments
Strong understanding of Machine Learning, with the ability to collaborate deeply with Data Scientists on model deployment and optimization
Experience with MLflow for experiment tracking and model management
Experience with Airflow or Dagster for orchestrating end-to-end ML pipelines and workflows
Significant experience with Data Engineering, Kafka, and stream processing
Proficiency in Python and SQL

Nice To Haves

Any other programming languages is a strong plus

Responsibilities

Mentor and guide mid-level Machine Learning Engineers, providing technical leadership and helping to shape best practices across the organisation.
Conduct comprehensive code reviews, identifying areas for improvement, and fostering a culture of continuous learning and collaboration.
Communicate effectively with both technical and non-technical stakeholders, translating complex machine learning concepts into actionable business insights.
Present innovative solutions to key stakeholders, making compelling cases for new initiatives and guiding the strategic direction of our machine learning efforts.
Lead the integration of new technologies and tools into our infrastructure, staying ahead of industry trends and ensuring that our machine learning frameworks remain at the cutting edge of technological advancements.
Take a leadership role in shaping the strategic direction of our machine learning infrastructure.
Proactively identify opportunities for innovation and improvement.
Drive the development of cutting-edge solutions that enhance the performance, scalability, and reliability of our machine learning systems.
Ensure that models are deployed seamlessly, optimized for production environments, and meet the highest standards of efficiency and accuracy at scale.
Architect and oversee the development of complex machine learning pipelines.
Manage both real-time and batch inference systems that are integral to our predictive platforms.
Work closely with cross-functional teams to anticipate future needs, recommending and implementing long-term solutions that align with our business objectives.