Student machine learning software engineer building end - to - end AI solutions at RBC Borealis, Royal Bank of Canada’s AI and data innovation group. Collaborating with researchers and business teams on algorithms, distributed data processing, and production - ready software.
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Software Developer Specialist – Machine Learning Infrastructure, Deployment
Posted 4 months ago
About the role
- Software Developer Specialist focusing on ML Infrastructure and Deployment at Verafin. Engaging with analytics teams to develop fraud detection products with DevOps and MLOps principles.
Responsibilities
- Design, implement, and maintain scalable cloud pipelines using AWS, Jenkins, and Terraform to support machine learning development, testing, and deployment.
- Partner closely with analytics teams as a subject matter expert to enable the development, deployment, and operation of machine learning products.
- Lead incident response and root-cause analysis efforts, implementing solutions that reduce downtime and prevent recurring issues.
- Build and optimize configuration management, automation frameworks, and deployment processes to ensure consistency, reliability, and maintainability.
- Ensure strong data governance, security compliance, and access control across all data and ML environments.
- Optimize cloud infrastructure for performance and cost efficiency, with a focus on long-term scalability and operational excellence.
- Lead projects and independently own technical decisions for ML infrastructure components, while mentoring junior engineers through code reviews, design discussions, and best practices.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
- 5+ years of experience in Cloud Development, DevOps, or related roles, with deep hands‑on expertise building and operating production AWS infrastructure using Terraform.
- Strong knowledge of AWS services used in ML and data platforms (e.g., VPC, Lambda, Step Functions, DynamoDB, EMR, RDS, Redshift, ElastiCache, SageMaker), including complex multi‑account architectures with networking, security, and access controls.
- Proficiency developing and supporting Java‑ and Python‑based microservices, with a solid understanding of SQL, databases, CI/CD pipelines (GitHub, Jenkins), and operational best practices.
- Excellent communication and problem‑solving skills, with experience in monitoring, alerting, and incident response, and the ability to work independently while clearly explaining technical trade‑offs to both technical and non‑technical stakeholders.
- Nice to Have Experience with SageMaker tool suite (Unified Studio, Pipelines, Model Registry, Endpoints).
- AWS EMR development experience with Java or Scala for large-scale data processing workloads.
- Additional certifications in DevOps, AWS, Terraform, or related technologies.
Benefits
- Flexible work arrangements
- Professional development opportunities
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