Mumbai, Maharashtra, India
Information Technology
Full-Time
VectorStack
Overview
Skills:
AWS, ETL, python, PyTorch, React.js, API, REST APIs, MLflow,
Python Full Stack Developer Cloud & AI Integration 3- 5 years
We are looking for a dynamic Python Full Stack Developer to join our engineering team. This role blends full stack development with cloud-native architecture and AI/data science integration. Youll work on scalable web applications, deploy intelligent services on AWS, and collaborate with data scientists to bring machine learning models into production.
Key Responsibilities
AWS, ETL, python, PyTorch, React.js, API, REST APIs, MLflow,
Python Full Stack Developer Cloud & AI Integration 3- 5 years
We are looking for a dynamic Python Full Stack Developer to join our engineering team. This role blends full stack development with cloud-native architecture and AI/data science integration. Youll work on scalable web applications, deploy intelligent services on AWS, and collaborate with data scientists to bring machine learning models into production.
Key Responsibilities
- Develop and maintain scalable web applications using Python (Flask/Django/FastAPI) and modern JavaScript frameworks (ReactJS).
- Design and implement RESTful APIs and microservices for AI-driven applications.
- Integrate machine learning models and data pipelines into production environments.
- Leverage AWS services (Lambda, S3, EC2, API Gateway, SageMaker) for cloud-native development.
- Collaborate with data scientists and DevOps engineers to deploy and monitor AI solutions.
- Ensure application security, performance, and scalability.
- Participate in code reviews, agile ceremonies, and continuous improvement initiatives.
- Proficiency in Python and JavaScript (React JS preferred).
- Excellent problem-solving and communication skills.
- Expert in Python Programming, Deployment of AI solutions and AI engineering
- Experience with backend frameworks like Django, Flask, or FastAPI.
- Solid understanding of AWS services and serverless architecture.
- Familiarity with AI/ML workflows and tools (e.g., TensorFlow, PyTorch, scikit-learn).
- Experience with CI/CD pipelines and containerization (Docker, Kubernetes).
- Strong problem-solving skills and ability to work in cross-functional teams.
- Bachelors or Masters in Computer Science, Engineering, or related field.
- Exposure to MLOps practices and tools (e.g., MLflow, SageMaker Pipelines).
- Experience with data visualization libraries and BI tools.
- Knowledge of data engineering concepts (ETL, data lakes, streaming).
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