FINVASIA - Artificial Intelligence Engineer

Description

Job Overview

Key Responsibilities

• Develop Generative AI applications such as Retrieval-Augmented Generation (RAG) systems, AI agents, and LLM fine-tuning pipelines.
• Design and implement Machine Learning models for regression, classification, and time series forecasting tasks.
• Work with LLMs (e.g., GPT, BERT, LLaMA) and integrate them using frameworks like LangChain, Hugging Face, and OpenAI APIs.
• Leverage vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and similarity-based retrieval.
• Build and maintain automated AI/ML pipelines for data preprocessing, training, evaluation, and deployment.
• Implement prompt engineering and fine-tuning strategies for task-specific LLM performance improvements.
• Knowledge of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) to manage structured and unstructured data.
• Understanding of Statistics, including hypothesis testing, distributions, and statistical modelling techniques essential for building robust ML models.
  

Required Skills & Experience

• Strong knowledge of supervised and unsupervised learning algorithms with real-world application experience.
• Strong Proficiency in Python and machine learning libraries such as scikit-learn, TensorFlow, PyTorch, Pandas, and NumPy.
• Hands-on experience with LLMs, embedding models, and retrieval-based architectures.
• Proficient in vector search technologies and building GenAI-powered applications.
• Experience deploying models on AWS or similar cloud platforms.
• Familiarity with version control (Git), DevOps principles, and agile workflows.
  

Preferred Skills

• Collaborate with cross-functional teams to translate business problems into scalable AI solutions.
• Strong understanding of SDLC, containerization, and model monitoring in production.
• Exposure to FinTech or financial services use cases involving real-time or compliance-heavy data.
• Ability to work with Product managers, Stakeholders and Data engineering teams to frame AI-first solutions for complex business problems.
  

Educational Qualifications

• Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.