ML Architect

Job Title: Architect/ Sr. Architect - ML
Location: Pune
Employment Type: Full-Time
Experience: 8-12 Years

About the Role
We are hiring an ML architect with deep expertise in Ontology Engineering,
Knowledge Graphs, Entity Disambiguation, Semantic Systems, and NLP to build
enterprise-grade intelligent platforms.
This role is ideal for someone who has moved beyond experimental ML and has built
production-scale semantic AI systems for large datasets and complex business
domains (BFSI, Healthcare, Retail, Enterprise SaaS, etc.).
You will play a key role in architecting structured knowledge-driven AI systems that
power contextual search, reasoning engines, and next-generation AI applications.

Key Responsibilities
Design and implement domain ontologies and semantic models aligned to
business use cases
Build and scale Knowledge Graph architectures (RDF/OWL/SPARQL
preferred)
Develop advanced Entity Detection & Entity Disambiguation (ED) pipelines
Implement NLP models for semantic understanding, information extraction, and
entity linking
Integrate Knowledge Graphs with ML pipelines and LLM-based applications
Develop scalable, production-ready ML systems using Python (mandatory)
Work closely with data engineering teams on data ingestion, transformation, and
graph population
Ensure explainability, governance, and semantic consistency in AI systems
Mentor junior engineers and contribute to architectural decisions

Must-Have Technical Skills

Core Expertise
8-12 years of hands-on experience in ML / AI Engineering
Strong practical experience in:
Ontology design and modeling
Knowledge Graph construction and maintenance
Entity Recognition & Entity Disambiguation
Semantic reasoning systems
NLP (NER, relation extraction, classification)
Programming
Expert-level Python (mandatory)
Experience with ML frameworks (PyTorch / TensorFlow / Scikit-learn)
Experience with NLP libraries (SpaCy, Hugging Face, NLTK, etc.)
Knowledge Graph & Semantic Stack
RDF / OWL / SPARQL
Graph databases (Neo4j, Blazegraph, Amazon Neptune, etc.)
Experience with ontology tools (Protg or similar)

Production & Cloud
Experience deploying ML models to production
REST APIs / microservices architecture
Cloud exposure (AWS / Azure / GCP)
CI/CD understanding for ML systems

Good to Have:
Experience in enterprise AI deployments
Exposure to LLM + Knowledge Graph integration
Experience handling multilingual NLP (especially Indian languages)
Familiarity with data governance and regulatory environments
Experience working in global delivery models

Ideal Candidate Profile
Strong system design and architecture thinking
Ability to translate ambiguous business problems into scalable AI solutions
Comfortable working with large structured + unstructured datasets
Strong communication skills to work with global stakeholders
Experience mentoring or leading small teams

Why This Role is Strategic
India is seeing rapid growth in:
Enterprise AI
Knowledge-driven systems
Semantic search platforms
LLM + structured data integration
This role directly contributes to building next-gen AI systems beyond traditional ML
pipelines.