Data/Machine Learning Infrastructure Engineer

Summary

Join Wavelo, a SaaS company within Tucows, as a Data/AI Infrastructure Engineer. You will build and optimize infrastructure for large-scale event processing, enabling machine and deep learning for real-time insights. Key responsibilities include deploying AI models, integrating with Kafka, managing model training, collaborating with cross-functional teams, monitoring performance, and documenting processes. This role requires 3+ years of experience in AI/ML deployment and expertise in Kafka, various AI/ML frameworks, and data engineering. Preferred qualifications include experience with CI/CD, GoLang, and real-time processing frameworks. The position offers a competitive salary and a comprehensive benefits package.

Requirements

• Have extensive experience with machine learning, deep learning, and AI data processing clusters, including Apache Spark and other relevant technologies
• Be deeply passionate about AI and have exposure to training models either locally or through cloud platforms like Google Vertex AI, AWS SageMaker, or Azure ML
• 3+ years in AI/ML deployment, solutions engineering, or similar roles, with hands-on experience in Kafka and event-stream integration
• Proficiency with Apache Kafka for setting up, managing, and scaling event-stream pipelines
• Familiarity with LangChain and related AI/ML frameworks (TensorFlow, PyTorch, scikit-learn) and cloud environments (AWS, Azure, Google Cloud)
• Experience in RESTful APIs, microservices, and containerization technologies such as Docker and Kubernetes
• Solid grounding in data engineering practices, with a strong emphasis on handling and cleaning messy, unstructured data to ensure quality for downstream machine learning tasks. Experience in feature engineering and continuous model improvement is essential, as this role will involve significant effort in preparing complex data for large-scale processing
• Analytical and proactive approach to resolving integration and performance challenges
• Strong ability to convey technical concepts to both technical and non-technical stakeholders, with a collaborative and team-oriented mindset

Responsibilities

• Deploy AI and machine learning models within Wavelo’s production environment, aligning with our software architecture to drive actionable insights from our telecom event streams
• Develop and maintain Kafka pipelines to support real-time data processing, facilitating the flow of critical insights and enabling swift actions on event-stream data
• Manage model training, tuning, and retraining workflows, ensuring that models are optimized to capture actionable insights from our event streams
• Work with data engineers, product teams, and other stakeholders to align on data needs, model requirements, and integration objectives
• Develop and implement monitoring solutions for model performance within the event-stream environment, identifying and resolving issues proactively
• Document processes, model configurations, and best practices to promote knowledge sharing and continuous improvement across Wavelo

Preferred Qualifications

• Experience with CI/CD pipelines and automated deployment processes
• GoLang experience
• Event-Driven Architecture experience
• Familiarity with real-time processing frameworks like Apache Spark or Flink
• Prior experience in using AI for real-time data analysis or IoT applications, particularly in the telecom space

Benefits

• Competitive salary ($200,000 - $225,000 USD for US residents OR $167,000 - $185,000 CAD for Canadian residents)
• Comprehensive benefits package
• Remote-first work environment