Job Title : AI/ML Engineer
Experience- 4 to 10 years
Location: Vashi, Navi Mumbai (Work from Office)
Key Responsibilities
- Design and implement RAG pipelines, including support for multimodal inputs such as text, tables, and images.
- Build AI applications that process unstructured financial documents (e.g., PDF, Word, scanned files) to extract insights, generate content, and enable Q&A.
- Develop solutions that convert financial documents into structured regulatory formats like XBRL/iXBRL.
- Integrate LLMs into production systems using FastAPI or similar frameworks.
- Use OCR techniques to extract information from scanned documents and embedded images.
- Collaborate with data scientists, engineers, and product managers to deliver business-aligned AI solutions.
- Optimize model performance for scalability, accuracy, and cost-efficiency.
- Contribute to the architecture and design of AI systems and participate in technical decision-making.
- Keep up to date with advancements in AI/ML, especially in the areas of RAG, multimodal processing, and LLMs.
Mandatory Skills and Qualifications
- 5+ years of experience in AI/ML engineering or related roles.
- Hands-on experience with RAG pipelines, including chunking, embeddings, vector databases, and query response optimization.
- Experience working with unstructured data (PDFs, scanned documents, images) and converting them into structured information.
- Strong knowledge of OCR techniques and tools for processing scanned documents.
- Proficiency in developing APIs using FastAPI (or similar frameworks) for AI model integration.
- Experience deploying AI solutions in containerized environments (Docker and Kubernetes).
- Familiarity with financial documents such as annual reports, and ability to work with domain-specific concepts like revenue, balance sheets, etc.
- Experience with at least one vector database (Qdrant preferred, others acceptable).
- Understanding of multimodal AI techniques and experience working with both text and image-based inputs.
- Strong communication and problem-solving skills, with the ability to work in cross-functional teams.
Preferred Skills (Good to Have)
- Experience with LLM fine-tuning techniques such as SFT, PEFT, or LoRA.
- Knowledge of model development using PyTorch or TensorFlow.
- Familiarity with LangChain, LlamaIndex, CrewAI, AutoGen, or similar LLM orchestration frameworks.
- Exposure to Azure OpenAI, OpenAI APIs, or similar cloud-based LLM providers.
- Experience with MLOps practices, including model lifecycle management and monitoring.
- Prior work on time series forecasting or classical ML models (e.g., using Scikit-learn).
- Familiarity with Azure Document Intelligence or similar document AI platforms.
- Experience working on multilingual or translation-based LLM systems.
- Contributions to open-source AI/ML projects or relevant published research.
Educational Qualifications:
Bachelor's or master's degree in:
- Computer Science / Engineering
- Mathematics
- Statistics or related quantitative fields
