Machine Learning Engineer - 4

Tide · Hyderabad

  • Experience7–11 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelexecutive
  • Posted2 Sept 2026
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About Tide

Tide is hiring in Hyderabad in financial services. This role looks for around 7+ years of experience.

Skills

  • Python
  • Java
  • machine learning
  • Django
  • FastAPI
  • Flask
  • REST APIs
  • CI/CD pipelines
  • GitHub Actions
  • event-driven architectures
  • AWS
  • Object-oriented programming
  • SOLID

The role

A machine learning engineer at a financial services product company integrates trained machine learning models into backend services and builds REST APIs with Django and FastAPI, while also developing event-driven architectures and CI/CD pipelines.

Full job description

Responsibilities:

Working closely with product owners, other backend (Java and Python) engineers, data scientists, and other business members to translate requirements into well-engineered solutions.

Architect, design, test, implement, deploy, monitor, and maintain end-to-end backend services. You build it, you own it mentality.

Integrate already trained ML models in some of the services you develop.

Work with people from other teams and departments on a day-to-day basis to ensure efficient project execution with a focus on delivering value to our members.

Regularly aligning your team's vision and roadmap with the target architecture within your domain to ensure the success of complex multi-domain initiatives.

Requirements:

You have 8+ years of experience as a Backend Python Engineer (Senior/Lead).

You have an understanding of software engineering fundamentals (OOP, SOLID, etc. ).

You have hands-on experience with frameworks such as Django, FastAPI, or Flask.

You have extensive experience integrating with or creating REST APIs.

You have experience with creating and maintaining CI/CD pipelines - we use GitHub Actions.

You have experience with event-driven architectures.

You have experience with AWS.

(Great to have) Experience with Databricks, ML feature store solutions, and Kafka (or other message brokers).