About the Role

We are looking for a strong AI Engineer / Machine Learning Engineer to contribute to the development of intelligent, enterprise-wide search systems and production-grade ML solutions. The role involves working across NLP, semantic search, embeddings, LLMs, RAG, ranking, personalization, and recommendation systems to improve search relevance and user experience.

The ideal candidate should have strong hands-on expertise in Python, SQL, Machine Learning, NLP, and production AI/ML systems, with the ability to work closely with Product, Engineering, Design, and Business teams.

Key Responsibilities

- Contribute to the development and optimization of enterprise-wide search systems and AI/ML models.
- Design and implement algorithms to improve indexing, query relevance, ranking, and search accuracy.
- Build and optimize solutions involving semantic search, embeddings, vector retrieval, and knowledge retrieval.
- Support the creation and refinement of taxonomies, ontologies, metadata models, and knowledge structures for improved search outcomes.
- Collaborate with business teams across Loans, Insurance, Investments, and other financial services domains to develop AI-enabled search capabilities.
- Analyze user behavior, search patterns, and system metrics to identify opportunities for improving search performance.
- Develop production-grade ML systems for ranking, personalization, recommendations, and search relevance.
- Build and implement RAG-based solutions involving chunking, indexing, retrieval, and contextual generation.
- Collaborate with Engineers, Product Managers, Designers,



and Business teams to deliver integrated AI/search solutions.
- Participate in proof-of-concept initiatives with internal teams and external technology partners.
- Follow software engineering best practices including Git, CI/CD, testing, monitoring, and production deployment.
- Stay updated with emerging developments in AI/ML, NLP, LLMs, and intelligent search and apply relevant technologies to practical business problems.

Mandatory Requirements

- 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
- Strong hands-on experience in Python, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
- Experience with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
- Hands-on experience with NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
- Experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
- Hands-on experience building or implementing RAG systems, vector search,



knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
- Experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
- Robust problem-solving skills and ability to work effectively as an Individual Contributor.
- Age: Candidate should be below 28 years.
- Education: B.Tech/M.Tech from Tier 1 institutions, preferably IITs, NITs, or BITS.

Preferred Qualifications

- Experience with MLflow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or other MLOps/LLMOps frameworks.
- Experience with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems.
- Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architectures.
- Experience in enterprise search, recommendation, ranking, personalization, or information retrieval is a strong advantage.
- Candidates from AI-first startups, FinTech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies are preferred.

Compensation The compensation structure will be 75% Fixed + 25% Variable, as per company policy.

Ideal Candidate The ideal candidate is a hands-on AI/ML Engineer with strong expertise in Python, NLP, LLMs, RAG, semantic search, and production ML systems, who can work on enterprise-scale search and intelligent retrieval problems and translate business requirements into scalable AI solutions

📌 Associate Lead - AI/ML Engineer ( Python, AL/ML) (Maharashtra)
🏢 Bajaj FinServ
📍 Maharashtra