Machine Learning Engineer (SDE 2)
Indexed description
This is a hands-on engineering role. You'll spend most of your time writing production Python, building and maintaining APIs, making architectural decisions, and collaborating closely with data scientists and product teams to ship ML-powered features.
About The Work
- Own the end-to-end lifecycle of ML microservices—from design through deployment and monitoring
- Build and maintain APIs that serve ML models to internal and external consumers
- Partner with data scientists and product teams to translate business requirements into technical solutions
- Write clean, efficient, and maintainable code that others can build on
- Take ownership of and improve our existing codebases, systems, and workflows
- Communicate technical concepts clearly to both engineers and non-technical stakeholders
- Bachelor's degree in Computer Science or equivalent
- 3–5+ years of backend engineering experience, with at least 3 years in Python
- Strong experience building APIs with Flask or FastAPI
- Solid experience with databases and SQL (PostgreSQL, MySQL, or similar)
- Experience with cloud platforms (AWS/GCP)
- Hands-on experience with message queues (RabbitMQ, Kafka, or SQS), Docker, and CI/CD pipelines
- Familiarity with monitoring tools (Datadog, Grafana) for tracking latency, errors, and alerts
- Experience deploying ML models in production
- Clear communication and collaboration skills
- Startup experience
- Fintech background
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