HyrEzy Talent Solutions
Python & AI Developer - Remote
India
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- Role family
- Engineering
- Seniority
- Mid level
- Stated salary
- ₹2,000,000 – ₹3,200,000 per year
- Country
- IN
- Work mode
- Remote-friendly
- First seen by hirly
- 26 Sept 2026
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the posting
Python & AI Developers
Department: Software Engineering & Artificial Intelligence
Experience Required: 3 to 6 Years
Compensation (Market Standard): INR 2,000,000 to 3,200,000 Per Annum (CTC)
Locations: Bangalore / Pune / Hybrid / Remote-flexible across India
Role Overview & Key Responsibilities
We are looking for a versatile Python & AI Developer to write clean, maintainable, and high-performance code that powers our core AI applications and backend services. You will work closely with data scientists and machine learning engineers to turn experimental code and complex algorithms into robust, production-ready software systems capable of scaling seamlessly under heavy loads.
Backend Development: Build robust backend services, microservices, and asynchronous task workers using modern Python frameworks (FastAPI, Django, or Flask).
AI Model Serving: Develop optimized serving layers for machine learning models and LLMs, ensuring fast inference speeds and low latency.
Data Pipelines: Construct reliable ETL pipelines to ingest, clean, and process structured and unstructured data feeds for downstream AI consumption.
Testing & Quality Assurance: Write comprehensive automated test suites (pytest), perform code reviews, and maintain high standards of code hygiene and documentation.
CI/CD & Deployment: Containerize applications using Docker and manage deployments across cloud environments using standard CI/CD pipelines.
Required Skills & Experience
Programming Skills: 3 to 6 years of commercial software development experience with expert-level proficiency in Python.
Framework Experience: Hands-on experience building RESTful web services, handling JSON data, and working with relational or NoSQL databases.
AI Tooling Exposure: Familiarity with integrating machine learning models, third-party AI APIs, and data processing libraries (Pandas, NumPy).
DevOps Basics: Comfortable working with Docker, Git version control, Linux environments, and cloud infrastructure basics.
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