Domain: Risk-Model Ecosystem
Work Mode: Remote
Experience: 10+ Years
Role Overview
We are looking for a highly skilled and hands-on Lead AI/ML Engineer with deep expertise in Databricks, Generative AI, LLMs, and model development.
The role will focus on building a semantic evaluation capability for risk models using proprietary enterprise data and domain knowledge.
This is a model-layer focused role, requiring solid technical depth in AI/ML model development rather than AI platform or infrastructure engineering.
Key Responsibilities
- Lead the end-to-end AI/ML model development lifecycle
- Work extensively on data preparation, pre-training, fine-tuning, and foundation models
- Design and implement GenAI/LLM solutions using models such as Claude and Llama
- Develop RAG architectures and domain-specific LLM solutions
- Leverage Databricks for AI/ML development and experimentation
- Apply AI/ML solutions to complex risk-model ecosystems
- Work with proprietary enterprise data and domain-specific knowledge
- Provide deep technical leadership and collaborate with senior technical stakeholders, including the CTO
Must-Have Skills
- 10+ years of overall experience in AI/ML
- Strong, hands-on Databricks experience
- Proven experience across the AI/ML model lifecycle
- Robust knowledge of:
- Data preparation
- Model pre-training
- Fine-tuning
- Foundation models
- LLMs
- Generative AI
- RAG
- Domain-specific AI/LLM solutions
- Experience with models such as Claude, Llama, or similar foundation models
- Strong Python and machine learning expertise
- Ability to work at the model development layer, beyond off-the-shelf AI platforms
Preferred Qualifications
- Experience in financial services, consumer credit, or risk-modeling ecosystems
- Experience working with AWS + Databricks
- Exposure to enterprise-scale proprietary datasets and domain-specific AI applications
📌 Lead Machine Learning Engineer - Databricks & Gen AI (India)
🏢 Inumellas Consultancy Services
📍 India
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