Sr. Python Developer

AI/ML Development:

1. Model Development and Training:
2. Design, develop, and train machine learning models and algorithms to solve specific business problems.
3. Implement various machine learning techniques including supervised, unsupervised, and reinforcement learning.
4. Data Preprocessing and Analysis:
5. Perform data cleaning, transformation, and preprocessing to prepare data for model training.

6. Analyze and interpret complex data sets to identify patterns and trends. - NLP, nltk and NER are preferred.

7. Model Evaluation and Optimization:

8. Evaluate model performance using appropriate metrics and fine-tune models to improve accuracy and efficiency.

9. Implement model optimization techniques such as hyperparameter tuning and feature engineering.

10. Deployment and Maintenance:

11. Deploy machine learning models into production environments ensuring scalability and reliability.
12. Monitor and maintain models to ensure they continue to perform well over time.

Python Development:

Software Development:

- Write clean, maintainable, and efficient Python code.

- Develop and maintain Python-based applications, APIs(Flask and Fast API preferred) , and microservices.

Code Review and Mentorship:

- Conduct code reviews to ensure adherence to best practices and coding standards.

- Mentor junior developers and provide guidance on best practices and development techniques.

Integration and Testing:

- Integrate machine learning models with existing systems and applications.

- Develop and execute unit tests, integration tests, and end-to-end tests to ensure software quality.

Automation and Scripting:

- Automate repetitive tasks and workflows using Python scripts.

- Develop and maintain automation tools and frameworks.

Collaboration and Communication:

- Collaborate with data scientists, data engineers, product managers, and other stakeholders to

understand requirements and deliver solutions.

- Participate in design and architecture discussions to shape the direction of projects.

Documentation and Reporting:

- Document code, processes, and methodologies to ensure knowledge sharing and maintainability.

- Communicate findings, progress, and results to stakeholders through reports and presentations.

Continuous Learning and Improvement:

1. Stay Updated with Industry Trends:

- Keep up-to-date with the latest developments in AI/ML and Python technologies.

- Experiment with new tools, libraries, and frameworks to improve existing solutions and processes.

Problem Solving and Innovation:

1. Innovative Solutions:

- Identify opportunities to apply AI/ML techniques to solve new and existing problems.

- Propose and implement innovative solutions to improve business processes and outcomes.

2. Technical Challenges:

- Tackle complex technical challenges and provide effective solutions.

- Troubleshoot and resolve issues related to machine learning models and Python applications.

Mandatory Skills:

Strong proficiency in Python and its libraries (e.g., NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch).

NLP, nltk and NER hand on knowledge is required.

Experience with data preprocessing, feature engineering, and model evaluation.

Knowledge of software development principles, design patterns, and best practices.

Excellent problem-solving and analytical skills.

Strong communication and collaboration abilities.

Ability to work independently and as part of a team.

Continuous learning mindset and adaptability to new technologies.