About this role
Build and deploy foundational AI/ML models and scalable ML pipelines at Wave, a FinTech company helping small businesses thrive. You'll work with AWS SageMaker, Databricks, and modern MLOps tools to productionize machine learning systems.
Must have
Minimum 3-5 years professional experience in machine learning engineering with production deployment track record
Deep understanding of modern data stack including data ingestion workflows and curated data warehouses
At least 3 years hands-on experience with AWS infrastructure specifically SageMaker Spark AWS Glue and IaC Terraform
High proficiency in managing multi-stage workflows using Airflow or similar orchestration systems
Practical experience with MLflow Kubeflow or SageMaker Feature Store for end-to-end ML lifecycle
Familiarity with model governance practices including lineage fairness and privacy
Strong ability to communicate complex technical concepts to non-technical stakeholders
Experience in FinTech or Financial Risk environments is a significant advantage
Technologies
Responsibilities
Build train and operationally deploy machine learning models ensuring reliable production performance
Advocate for top-tier practices across coding testing and MLOps processes
Construct resilient cost-efficient ML and AI use cases balancing sustaining models with scaling new systems
Partner with cross-functional stakeholders including risk specialists product leads and software developers
Uphold stringent benchmarks for model dependability fairness and compliance
Formulate comprehensive observability systems to capture model health and key operational metrics
Benefits
Recruitment process
Wave helps small businesses thrive so the heart of communities beats stronger
Work in an environment buzzing with creative energy and inspiration
No matter where you are or how you get the job done you have what you need to be successful and connected
The mark of true success at Wave is the ability to be bold learn quickly and share your knowledge generously
Wave values diversity of perspective and welcomes applicants from all backgrounds
Wave uses Google Gemini a secure AI assistant during interviews for note-taking purposes only
Notes are kept confidential and are not shared outside the hiring process
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