Bangalore, Karnataka, India
Information Technology
Full-Time
VectorStack
Overview
About the Role:
We are seeking a highly skilled and innovative Python Full Stack Developer to join our engineering team. This role requires a strong foundation in full stack development with a focus on cloud-native applications and AI integration. You will play a critical role in building scalable web solutions, integrating machine learning models, and working closely with data scientists and DevOps teams to bring intelligent services to production.
Key Responsibilities:
- Develop and maintain scalable and responsive web applications using Python (Flask, Django, or FastAPI) and ReactJS.
- Design, build, and maintain RESTful APIs and microservices to support AI-driven applications.
- Deploy and integrate machine learning models and data pipelines into production environments.
- Utilize AWS cloud services (Lambda, S3, EC2, API Gateway, SageMaker, etc.) for cloud-native application development.
- Collaborate with cross-functional teams including data scientists, DevOps engineers, and product managers to deliver AI-powered features.
- Optimize applications for performance, scalability, and security.
- Participate in agile ceremonies, perform code reviews, and contribute to continuous improvement initiatives.
Required Skills:
- Strong proficiency in Python and JavaScript (ReactJS preferred).
- In-depth knowledge of backend frameworks such as Django, Flask, or FastAPI.
- Hands-on experience with cloud-native development using AWS.
- Good understanding of AI/ML workflows and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Proficiency in containerization tools (Docker, Kubernetes) and experience with CI/CD pipelines.
- Solid knowledge of application performance, scalability, and security best practices.
- Excellent communication skills and the ability to collaborate effectively in a team environment.
Preferred Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Exposure to MLOps tools and practices (e.g., MLflow, SageMaker Pipelines).
- Experience with data visualization tools and BI platforms.
- Understanding of data engineering concepts such as ETL, data lakes, and real-time data streaming.
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