Revolo Infotech - Artificial Intelligence Engineer - Python/NLP (5-6 yrs)

Key Responsibilities :

AI/ML Model Development :

- Design, develop, and train machine learning models for key banking applications (e. , fraud detection, credit scoring, personalized financial advice, customer service automation).

- Fine-tune pre-trained models and build custom AI solutions as needed.

- Build Knowledge Index and fine tune LLMs with it.

Data Preparation and Analysis :

- Work with structured and unstructured financial datasets to preprocess, clean, and analyze data for AI/ML applications.

- Implement feature engineering techniques to enhance model performance.

Model Deployment :

- Deploy AI/ML/LLM models into production environments using MLOps best practices.

- Monitor, maintain, and improve model performance post-deployment.

Collaboration :

- Collaborate with product managers, software engineers, and domain experts to align AI capabilities with business requirements.

- Contribute to brainstorming sessions for innovative AI solutions.

Documentation and Reporting :

- Document workflows, models, and results for internal use and audits.

- Provide regular updates on project progress and insights.

Skills and Qualifications:Required :

- Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

- 5+ year of total experience and 3+ years in AI/ML development (internships and projects count).

- Experience with NLP models (e., BERT, GPT) for text-based banking applications.

- Strong programming skills in Python, with experience in AI/ML libraries (e. , TensorFlow, PyTorch, Scikit-learn).

- Hands-on experience with data processing frameworks like Pandas and NumPy.

- Solid understanding of machine learning concepts, including supervised and unsupervised learning.

- Familiarity with version control tools (e. , Git) and cloud platforms (AWS, GCP, or Azure).

- Strong problem-solving skills and a startup mindset.

Preferred :

- Knowledge of time-series modeling for financial data.

- Familiarity with MLOps tools and frameworks (e. , MLflow, Kubeflow, or Docker).

- Background in fintech or banking is a plus.

- Understanding of cybersecurity and regulatory compliance in banking.