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We are looking for a Lead / Principal Backend Software Engineer to help automate and streamline the process of bringing new document types and machine learning models into a document verification and identity platform. This is a hands-on individual contributor role with high ownership and broad impact, working closely with ML, platform, and product stakeholders to turn complex workflows into reliable, scalable automation.
Job Responsibility:
Replace manual, slow onboarding processes with automated, reliable pipelines using modern CI/CD and cloud technologies
Design, build, and deploy production grade APIs and services within a microservices and or serverless architecture
Own your work end to end, from design through deployment, ensuring scalability, security, and performance
Automate testing and delivery through robust unit, integration, and performance test suites and quality gates
Document solutions clearly for internal stakeholders and external developers consuming public APIs
Partner closely with ML and engineering teams to integrate existing ML models and services into onboarding workflows
Improve release quality and enable faster, safer, and more scalable deployments through automation and testing
Collaborate cross functionally with product managers, researchers, and operations teams to translate ideas into production ready features
Participate in Agile ceremonies (stand ups, planning, retrospectives) and help drive continuous improvement
Requirements:
Bachelor’s degree in Computer Science (or equivalent practical experience)
Demonstrated senior level experience building and operating production backend systems
Senior level proficiency in Python, especially for automation, data processing, and ML related pipelines
Strong experience designing CI/CD driven, fully automated release pipelines with integrated testing and quality gates
Experience defining automated decision logic based on metrics or KPIs to support fully automated onboarding or release flows
Practical experience integrating ML workflows into existing production systems
Experience working with existing machine learning models for document analysis, computer vision, or similar unstructured data problems (evaluation, configuration, adaptation)
Hands on experience with AWS based environments, including scalability, reliability, and cost considerations
Strong Git proficiency and a disciplined approach to code review and collaboration
Strong spoken and written English
Nice to have:
Experience improving or automating data labeling strategies, including semi supervised or active learning approaches
Exposure to MLOps practices (experiment tracking, model versioning, ML specific CI/CD patterns)
Experience optimizing model training performance for concurrency, resource utilization, and cost efficiency
Familiarity with C++ based core systems and or Go based production services
Experience delivering features from user stories through to deployment in Agile environments
What we offer:
Flexible working format - remote, office-based or flexible
A competitive salary and good compensation package
Personalized career growth
Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
Active tech communities with regular knowledge sharing