Sr. Knowledge Graph (GT,GNN,GAT) PhD Expert

🚨 Hiring – Data Scientist | Python + Agentic AI

💼 Experience: 5+ Years

Must Have:

• Strong Data Science experience

• Python

• Agentic AI / AI Agents

• Generative AI / LLMs

• RAG / Vector Databases

• LangChain / LangGraph or similar Agent Frameworks

• Machine Learning & NLP

Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

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Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

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Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.

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Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

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Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

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Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.

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Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

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Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

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Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

Mandatory (Education) - B.TECH / M.TECH from Tier 1 Colleges (IIT, NIT, BITS, IIIT, DTU, NSUT) are considered.

Job Summary

The Data Scientist / Analyst Consultant will design, develop and deploy advanced analytics and AI/ML models to detect fraud, waste and abuse across the AB PM-JAY ecosystem. The role involves working with large volumes of claims, beneficiary, provider and transaction data, engineering fraud features, building and validating detection triggers, and converting model outputs into investigation-ready suspicious claims and cards. The Data Scientist will build triggers using advanced analytics techniques including NLP, OCR, Social Network Analysis and deep learning, support their validation with the National Anti-Fraud Unit (NAFU), and continuously improve model efficacy based on feedback and confirmed fraud outcomes.

Key Responsibilities

• Design, develop and deploy statistical and machine learning models for fraud, waste and abuse detection on scheme claims and card data.

• Perform advanced data analytics including clustering, classification, profiling, anomaly detection, predictive modelling, scoring, regression, link prediction, co-occurrence grouping, similarity matching and causal modelling.

• Develop fraud detection triggers using advanced analytics techniques such as NLP, OCR, Social Network Analysis and deep learning, and document trigger construct, logic and thresholds for review and approval.

• Apply both supervised and unsupervised learning approaches, training models on labelled historical fraud data and scheme ecosystem data.

• Conduct data profiling, quality assessment, cleaning, standardisation and feature engineering to create analysis-ready datasets.

• Execute triggers and models on claim and card data within defined turnaround timelines and generate case-level suspicious output with trigger reasons and evidence fields.

• Validate model outputs, assess false positive risk, calibrate thresholds and measure trigger efficacy against defined performance benchmarks. • Fine-tune and retrain models on the basis of subsequent events, reviewer feedback and confirmed fraud outcomes.

• Collaborate with medical experts, business analysts, subject matter experts and technology teams to translate domain knowledge and clinical rules into executable analytical logic.

• Prepare model documentation, trigger submission packs, dashboards and reports for internal review committees and client-facing evaluations. 

Preferred Skills

• Experience in healthcare analytics, health insurance claims analytics or fraud, waste and abuse detection.

• Experience in fraud analytics roles with a proven track record of developing and implementing fraud detection models and strategies.

• Knowledge of AB-PMJAY / health benefit packages / claims adjudication workflows.

• Exposure to Social Network Analysis, graph analytics or link analysis for collusion and network detection.

• Familiarity with OCR, image analytics and document forgery or duplication detection.

• Experience with model deployment, versioning and MLOps practices.

• Exposure to dashboarding and BI tools such as Power BI, Tableau or equivalent. 

Experience

• Minimum 5 years of experience in analytics and managing big data, out of which at least 3 years in developing AI/ML models.

• Demonstrable credentials of having worked on and developed AI/ML models independently.

• Experience in fraud analytics, anomaly detection or risk modelling will be preferred.

• Experience in healthcare, health insurance or government health scheme data will be an added advantage.

Strong AI Engineer / Machine Learning Engineer profiles.

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Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

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Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

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Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

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Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

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Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

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Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

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Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Strong Senior AI Engineer Profile with production-grade LLM and Python expertise

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Mandatory (Experience 1): Must have at least 3+ years of professional AI/ML engineering experience with demonstrated track record of delivering production-grade AI systems in real-world environments

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Mandatory (Tech skill 1): Must have strong programming skills in Python and SQL, with hands-on ML/data libraries (scikit-learn, pandas, numpy) and deep-learning frameworks (PyTorch or TensorFlow), plus REST API design

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Mandatory (Experience 2): Must have hands-on experience building and deploying production-grade ML/LLMs including RAG pipelines, document parsing, information extraction, and text processing on large-scale unstructured data (preprocessing, chunking, embeddings, feature engineering)

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Mandatory (Tech skill 2): Must have strong NLP / extraction-focused ML depth — transformers, embeddings, vector databases, RAG, LLM integrations, and agentic workflows.

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Mandatory (Tech skill 3): Must have hands-on experience with AWS (SageMaker, Bedrock, EC2, Lambda) and Azure (AI Foundry, Azure OpenAI) for model training, fine-tuning, deployment, and inference at scale

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Mandatory (Tech skill 4): Must have experience with multi-agentic frameworks / orchestration tools (Claude Code, LangGraph, LangChain, CrewAI)

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Mandatory (Tech skill 5): Must have hands-on experience with MLOps ecosystem including experiment tracking (MLflow, Weights & Biases), model versioning/registry, automated retraining, and CI/CD (GitHub Actions, Azure DevOps, Docker, Kubernetes)

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Mandatory (Tech skill 6): Must have experience with evaluation frameworks (precision, recall, F1, field-level accuracy) and iterative model improvement, plus AI observability (Prometheus, Grafana, SLOs).

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Mandatory (Team Leadership): Must have experience leading projects or teams, managing technical deliverables, and mentoring, with strong problem-solving in ambiguous challenges

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Mandatory (Education) - B.Tech or B.E. If graduated in BCA or BCS, they should have a Maters or Post graduation

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Mandatory (Company): B2B Tech/Consulting/B2B Software

ou will work closely with AI engineers, product teams, and domain experts to build intelligent document processing and knowledge automation solutions. Responsibilities include:

• Develop AI-powered document ingestion and processing pipelines.
• Build knowledge extraction engines using NLP, Machine Learning, and Generative AI.
• Develop document-to-knowledge compilers that transform PDFs, Word documents, policies, regulations, and manuals into structured knowledge.
• Build AI agents and Agentic AI workflows for enterprise automation.
• Develop rule extraction and rule generation frameworks from business documents.
• Create semantic search and enterprise knowledge retrieval solutions.
• Develop backend APIs and AI services using Python.
• Design and optimize document processing pipelines for scalability and performance.
• Build and maintain MySQL databases for knowledge repositories and AI applications.
• Integrate LLMs from providers such as OpenAI, Azure OpenAI, Gemini, Claude, and open-source ecosystems.
• Collaborate with cross-functional teams to design scalable AI architectures.
• Participate in code reviews and follow software engineering best practices.
• Continuously evaluate and adopt emerging AI and GenAI technologies.

REQUIRED SKILLS — PROGRAMMING & DEVELOPMENT

• Strong proficiency in Python and a solid understanding of Object-Oriented Programming (OOP).
• Experience building REST APIs and backend services.
• Experience working with JSON, XML, and structured data formats.
• Knowledge of software design patterns and scalable architecture.
• Strong debugging, analytical, and problem-solving skills.

ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

• Strong understanding of Machine Learning concepts and algorithms.
• Experience with Natural Language Processing (NLP) and Generative AI solutions.
• Hands-on experience with Large Language Models (LLMs).
• Understanding of prompt engineering techniques.
• Knowledge of Agentic AI concepts and AI agent architectures.
• Experience developing AI-powered applications and workflows.

TECHNOLOGY STACK

AI & GenAI: Python · OpenAI · Azure OpenAI · Hugging Face · Agentic AI Frameworks · LLMs · NLP · Machine Learning

Knowledge Systems: ChromaDB · Pinecone · FAISS · Vector Databases · Semantic Search

Document Processing: Docling · OCR · PDF Processing · Apache Tika · Document Intelligence

Backend: Python · FastAPI · Flask · REST APIs

Database: MySQL

Tools & Technologies: Git · Docker · JSON · CI/CD · Azure / AWS / GCP

PRINCIPAL AI ENGINEER @ METADOME.AI

Company Description

Metadome.ai builds frontier AI models that transform text, drawings, and CAD into production-ready, interactive 3D experiences. The company advances a full generative pipeline—text-to-CAD, 2D-to-3D

reconstruction, CAD completion and harmonization, and real-time interactive rendering—engineered for the precision required in the physical world. Its technology currently powers the modernization of

OEM aftersales for more than 30 automotive and heavy-equipment manufacturers worldwide, delivering accurate, scalable, and fast 3D solutions. Metadome.ai’s platform enables shoppable 3D parts, step-by-step repair animations, and a headless API that feeds consistent 3D assets into commerce, dealer, training, and service systems. The broader mission is to allow anyone to move from an idea, drawing, or specification to a production-grade 3D model and beyond in seconds.

Role Description

As a Principal AI Engineer — Generative CAD & 3D, you will lead the design, development, and deployment of advanced AI models that convert text, 2D drawings, and CAD files into engineering-grade 3D content. You will architect end-to-end generative pipelines, including

text-to-CAD, 2D-to-3D reconstruction, CAD completion, and real-time rendering, collaborating closely with product, design, and engineering teams to ship robust production systems. Day-to-day, you will experiment with novel neural network architectures, optimize model performance on large-scale CAD datasets, write high-quality production code, and guide the integration of AI services into customer-facing platforms. You will mentor other engineers, establish best practices for AI development, and contribute to technical strategy and roadmap. This is a full-time, hybrid role based in Bengaluru, with a mix of on-site collaboration and work-from-home flexibility.

Qualifications

• Strong foundation in Computer Science and Software Development, including data structures, algorithms, system design, and production-grade coding in languages such as Python, C++, or similar.
• Deep expertise in Neural Networks and Pattern Recognition, with hands-on experience designing, training, and deploying modern deep learning architectures for complex, high-dimensional data.
• Experience with Natural Language Processing (NLP), including working with text encoders, multimodal models, and integrating language understanding into generative workflows.
• Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, Applied Mathematics, or a related field, or equivalent practical experience in AI/ML research and engineering.
• Background in 3D geometry, CAD, computer graphics, or related domains, with familiarity in 3D representations, mesh processing, and rendering pipelines.

We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.

• Develop and implement machine learning and predictive analytics models.
• Perform data analysis, statistical modeling, and optimization to solve business problems.
• Build demand forecasting and predictive models using time-series and other advanced techniques.
• Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.
• Develop and maintain scalable data pipelines for ML model development and deployment.
• Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.
• Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.
• Validate models for accuracy, robustness, bias, and production readiness.
• Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.

• Python
• SQL
• Data Science & Machine Learning
• Predictive Modeling
• Statistical Analysis
• Machine Learning Algorithms
• Optimization Techniques
• Google Cloud Platform (GCP)
• BigQuery
• Dataflow
• Dataproc
• Data Fusion
• Cloud SQL
• Airflow
• PySpark
• PostgreSQL
• Terraform
• Tekton
• APIs
• MLOps

• Java

• Demand Forecasting
• Time-Series Analysis
• Neural Networks
• Ensemble Methods
• Support Vector Machines (SVM)
• Regression and Cluster Analysis
• ML Model Testing
• Bias Detection and Data Drift Monitoring
• Production ML Deployment
• QlikSense
• Automotive or Supply Chain Analytics

Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.

Job Summary

We are looking for an experienced AI/ML Engineer to design, develop, deploy, and maintain machine learning and AI solutions that address complex business problems. The ideal candidate should have strong hands-on experience in Python, Machine Learning, Generative AI, LLMs, and AI/ML deployment, with the ability to work across the complete AI/ML lifecycle.

Key Responsibilities

• Design, develop, and deploy scalable Machine Learning and AI models for real-world business use cases.
• Build and optimize ML pipelines covering data preparation, feature engineering, model development, evaluation, and deployment.
• Develop solutions using Generative AI, Large Language Models (LLMs), NLP, and deep learning.
• Work with LLMs, prompt engineering, embeddings, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
• Integrate AI/ML models with enterprise applications and APIs.
• Fine-tune and evaluate ML/LLM models based on business requirements.
• Implement MLOps practices for model versioning, deployment, monitoring, and continuous improvement.
• Collaborate with Data Scientists, Software Engineers, Architects, Product Managers, and business stakeholders.
• Conduct model performance evaluation, optimization, and troubleshooting.
• Ensure AI solutions meet requirements around security, scalability, reliability, responsible AI, and data privacy.
• Stay current with emerging AI/ML technologies, frameworks, and industry best practices.

Required Skills

• Strong programming experience in Python.
• Strong understanding of Machine Learning algorithms, statistics, and data structures.
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or equivalent.
• Experience with Generative AI and LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, or open-source models.
• Strong knowledge of Prompt Engineering, RAG, embeddings, vector databases, and AI agents.
• Experience with NLP, deep learning, or computer vision is an advantage.
• Experience developing and consuming REST APIs and microservices.
• Working knowledge of SQL and NoSQL databases.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Understanding of Docker, Kubernetes, CI/CD, and MLOps.
• Familiarity with Git and modern software development practices.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• 4 years of relevant experience in AI/ML engineering or a related field.
• Experience building and deploying production-grade AI/ML solutions.
• Enterprise application development experience.
• Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or similar managed AI platforms.
• Experience with LangChain, LlamaIndex, Semantic Kernel, or comparable AI frameworks is a plus.
• Experience with AI/ML model monitoring, evaluation, and optimization.

What You Bring

• Strong problem-solving and analytical skills.
• Ability to translate business requirements into practical AI/ML solutions.
• Strong software engineering and debugging capabilities.
• Ability to work independently as well as collaboratively in a cross-functional environment.
• Good communication skills with the ability to explain complex AI concepts to technical and non-technical stakeholders.

Keywords

AI Engineer | ML Engineer | Machine Learning | Generative AI | LLM | Python | NLP | Deep Learning | RAG | Prompt Engineering | AI Agents | Azure OpenAI | AWS Bedrock | MLOps | TensorFlow | PyTorch | Scikit-learn | Vector Database | Cloud AI

Location: Gurugram

Work mode: Hybrid

🚀 We’re Hiring | Data Scientist 🧠📊

Ready to turn data into real-world intelligence? Join us and work on exciting AI/ML & data-driven solutions!

🔹 Experience: 8+ Years

🔹 Must-Have Skills:

🐍 Python | 🤖 Machine Learning | ☁️ Cloud | 🧠 NLP | 📊 Data Visualization

📍 Location: Pune

💼 Work Mode: Work from Office

If you're passionate about Data Science, AI & solving complex business problems, we’d love to hear from you!

📩 Interested? Kindly text

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