Software Engineer II, Backend (ML Training & Serving)
New
CanadaFull-TimeMiddle
SalaryCAD $133,000 - $183,000 depending on experience, location, and skills
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Job Details
- Experience
- 1.5+ years
- Required Skills
- AWSPythonKotlinKubernetesMySQLDistributed Systems
Requirements
- 1.5+ years of professional experience as a software engineer or backend engineer.
- Experience designing, developing, testing, and launching backend systems in production environments.
- Proficiency in at least one backend programming language such as Python or Kotlin.
- Understanding of distributed systems concepts.
- Experience working with technologies such as AWS, MySQL, and Kubernetes.
- Ability to translate business requirements into technical solutions involving multiple software components.
- Strong coding skills with experience writing clean, maintainable, well-tested, and extensible software.
- Comfortable navigating large codebases, debugging existing systems, and providing constructive feedback through code reviews.
- Strong ownership mindset with a commitment to continuous learning and professional growth.
- Excellent written and verbal communication skills with the ability to collaborate effectively with global engineering teams.
- Experience with machine learning infrastructure, model training systems, or cloud-native platforms is a plus.
Responsibilities
- Design, develop, test, and launch reliable backend systems that support machine learning training and serving infrastructure.
- Break down complex engineering projects into actionable tasks, delivering solutions incrementally while collaborating with teammates and stakeholders.
- Build and maintain scalable distributed systems that improve reliability, performance, and developer efficiency.
- Collaborate with engineering teams to understand technical requirements, evaluate trade-offs, and make informed architectural decisions.
- Support production operations by creating monitoring solutions, tracking system performance metrics, and participating in on-call responsibilities when required.
- Contribute to improving platform capabilities that enable machine learning teams to develop and deploy models more effectively.
- Participate in code reviews, technical discussions, and knowledge-sharing activities to maintain high engineering standards.
- Engage in team growth initiatives, including mentoring, feedback sharing, and supporting the interview process.
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