Tide is hiring a
Backend Engineer(Machine Learning)

Summary

The job is for a Staff ML Engineer at Tide, a finance & admin platform. The role involves creating and maintaining distributed backend systems, developing microservices, collaborating in software architecture design sessions, participating in an agile development team, building an MLOps platform, and building complex data processing pipelines.

Requirements

• You have strong backend development experience and exposure to system design
• You have extensive development experience in Python, including development of microservices using a web-framework (Flask, FastAPI, etc)
• You have experience in building data solutions, both batch processes and streaming applications
• You have high development standards, especially for code quality, code reviews, unit testing, continuous integration and deployment
• You have experience working in an agile team, dedicated to generating value in an iterative fashion
• Business-level of English and good communication skills
• Experience with Git, Docker, and setting up CI/CD pipelines
• Exposure to Cloud providers - architecting solutions using managed services
• You are familiar with event-driven systems, with experience in Kafka or similar technologies
• Experience leading or mentoring a team of backend developers, coaching best practices and architecting solutions

Responsibilities

• Creating & maintaining distributed backend systems to operationalise ML models
• Developing & deploying low latency and scalable containerised microservices
• Collaborating in cross-functional software architecture design sessions to find the best solutions for the problems that we are facing
• Participating in an agile development team that delivers value iteratively, maintains and monitors prod systems
• Building an MLOps platform to speed up develop & deploy cycle and monitoring of models in production
• Building complex batch and streaming data processing pipelines

Preferred Qualifications

• You have worked with feature stores, ML Observability and/or automated MLOps systems
• Experience in batch processing/data frameworks (Airflow, Spark, Databricks, etc.)
• You have experience working with machine learning models, and know about the challenges faced when putting these into production

Benefits

• Competitive salary
• Self & Family Health Insurance
• Term & Life Insurance
• OPD Benefits
• Mental wellbeing through Plumm
• Learning & Development Budget
• WFH Setup allowance
• 15 days of Privilege leaves
• 12 days of Casual leaves
• 12 days of Sick leaves
• 3 paid days off for volunteering or L&D activities
• Stock Options