Python+MLOps Engineer
1 week ago
Role: Python+ MLOps Engineer
Experience: 5+years
Location: PAN India
Immediate joiners only
About the Project
The Content Amplify project is at the forefront of transforming unstructured financial narratives into structured, accessible data using cutting-edge AI technologies.
Our mission is to amplify human-in-the-loop efforts, enabling ML and LLM models to learn from subject matter expert feedback in a scalable, iterative process.
This includes leveraging ML-Ops, cloud-native architectures, and innovative feedback loops to continuously improve data quality, speed, and scope.
Key Responsibilities
- Develop scalable and maintainable Python-based backend systems. Build and optimize APIs and services using frameworks like Flask or Django.
- Collaborate with cross functional teams including Data Scientists, DevOps, Architecture, QA, Cyber Security etc. to integrate classic ML and LLM models into production workflows.
- Design and maintain efficient database schemas and queries.
- Implement security and data protection best practices.
- Debug, test, and improve existing systems.
- Support production systems and ensure high availability.
- Take full ownership of design initiatives — from concept to task breakdown.
- Ensure system reliability, fault tolerance, and performance optimization.
Must-Have:
•5+ years of experience as a Python developer.
•Proficiency in at least one Python web framework (Flask, Django).
•Strong understanding of ORM tools and relational databases.
•Experience with cloud platforms (Azure preferred, AWS acceptable).
•Solid SQL skills and query optimization techniques.
•Bachelor's degree in Computer Science, Engineering, or equivalent.
•Excellent problem-solving and collaboration skills.
•Experience with Kubernetes (EKS), Docker, and CI/CD pipelines.
•Experience building scalable data pipelines and integrating with ML workflows.
Nice-to-Have:
•Experience with big data technologies (Snowflake preferred).
•Familiarity with ML libraries (scikit-learn, pandas, PySpark, PyArrow).
•Ability to design and optimize database performance.
•Prior collaboration with Data Science teams.
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