Job Opportunities

Immediate Opening for Data Engineer (Module Lead/Technical Lead)

Technical Requirements

Experience -5 to 10 years

Core AI/ML: Expert-level proficiency in Python and leading AI/ML frameworks, including TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.

Strong understanding of supervised, unsupervised, and deep learning techniques, with experience developing, evaluating, and optimizing production-grade machine learning models.

LLMs & Generative AI: Hands-on experiencea with transformer-based foundation models (GPT, Llama, BERT, Mistral, etc.), prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning (LoRA/QLoRA), embedding models, and agentic AI workflows for domain-specific applications.

Data Engineering: Proficiency in working with structured, semi-structured, and unstructured data (JSON, XML, CSV, Parquet, documents).

Strong knowledge of SQL/NoSQL databases, vector databases, and graph data structures.

Experience with document processing, OCR pipelines, and specialized data extraction is a strong advantage.

Backend & AI Deployment: Experience exposing AI/ML models through

Roles and Responsibility

This role is not just about building AI models—it is about building the intelligence that powers the industrial backbone of the future.

You will solve real-world, high-impact challenges, from ensuring product design and manufacturing are safe and compliant to predicting supply chain disruptions before they impact critical operations or national security capabilities.

Data Exploration & Analysis Regulatory Text Interpretation Rule Formalization Natural Language Querying Retrieval-Augmented Generation (RAG) & Knowledge Engineering Forecasting & Demand Prediction Classification & Risk Scoring Data Engineering for AI AI Model Orchestration Performance Optimization Model Validation & Quality Assurance