Roles & Responsibilities:

- Contribute to the development and optimization of enterprise-wide search systems and models.
- Design and implement algorithms to improve indexing, query relevance, and search accuracy.
- Support taxonomy, ontology, and metadata model creation for better search outcomes.
- Collaborate with business units (Loans, Insurance, Investments) to build AI-enabled search features.
- Conduct analysis of user behavior and system metrics to refine search performance.
- Work with engineers, product managers, and designers to deliver integrated search solutions.
- Develop production-grade ML systems for ranking, personalization, and recommendations.
- Participate in proof-of-concept initiatives with internal and external partners.
- Follow best practices in software engineering including CI/CD, testing, and monitoring.
- Keep abreast of emerging developments in AI/ML to apply them in practical solutions.

Ideal Candidate:

1. Profile:

- Solid AI Engineer / Machine Learning Engineer profiles.

2.

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.

3.

Mandatory

Experience 2:

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

4.

Mandatory

Experience 3:

- Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

5.

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.

6.

Mandatory

Experience 5:

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

7.

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.

8.

Mandatory

Experience 7:

- Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

9. Mandatory CTC:

- The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

10.

Mandatory

Age:

- Candidate's Age should be below 30 Years.

11.

Preferred Experience 1:

- Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

12.

Preferred Experience 2:

- Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems.

13.

Preferred Experience 3:

- Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

14.

Preferred

Company:

- Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies.

15.

Mandatory

Pedigree:

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

📌 G Vak Softwares & Exports - Associate Lead - Artificial Intelligence/Machine Learning (India)
🏢 CG-VAK Software u0026 Exports
📍 India