AI​/ML Developer

is a fast-growing fintech platform on a mission to transform how businesses and individuals access credit and financial services. We leverage AI, big data, and cloud-native technologies to deliver secure, scalable, and intelligent financial solutions.

As part of our next growth phase, we are building AI-first capabilities across risk modeling, fraud detection, intelligent automation, and customer experience—powered by Generative AI and Large Language Models (LLMs).

This is your opportunity to shape the AI strategy from the ground up, working with cutting-edge technologies and seeing your work directly impact thousands of businesses.

Key Responsibilities

- AI/ML Development:
Architect and implement advanced ML systems for fraud detection, credit scoring, personalization, and risk modeling.
- Generative AI Solutions:
Build and deploy LLM-powered tools for financial document summarization, chatbot automation, KYC workflows, and customer support.
- LLM Experimentation:
Work with OpenAI, Claude, LLaMA, Mistral, etc.—covering prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG).
- MLOps & Deployment:
Own CI/CD for models, scalable serving, monitoring, and explainability (using MLflow, Kubeflow, or GCP/AWS/Azure ML stacks).

- Cross-Functional Collaboration:

Partner with product, compliance, and engineering teams to embed AI responsibly into fintech journeys.
- Model Governance:
Ensure fairness, bias mitigation, explainability (XAI), and adherence to financial regulatory standards.
- Team Leadership:
Mentor junior engineers and data scientists, fostering a high-performance AI culture.

Required Qualifications

- Bachelor’s or Master’s in Computer Science, AI/ML, or a related field.
- 4+ years building & deploying ML models in production, preferably in fintech or high-traffic domains.
- Strong skills in Python, Tensor Flow/PyTorch, and cloud ML services (GCP, AWS, or Azure).
- Hands-on expertise with LLMs, transformers, NLP techniques, embeddings, RAG pipelines, and vector databases (FAISS, Pinecone, Weaviate).
- Understanding of data privacy, compliance, fairness, and governance in AI for financial applications.