Eminds.ai - Generative AI/Machine Learning Engineer - LLM

Department : Technology / AI Innovation

Reports To : AI/ML Lead or Head of Data Science

Location : Pune

Role Summary :

- Design, develop, and deploy AI/ML models and Generative AI applications for diverse enterprise use cases.

- Implement, fine-tune, and integrate Large Language Models (LLMs) using frameworks like LangChain, LlamaIndex, and RAG pipelines.

- Build Agentic AI systems with multi-step reasoning and autonomous decision-making capabilities.

- Create secure and scalable data ingestion pipelines for structured and unstructured data, enabling indexing, vector search, and advanced retrieval.

- Collaborate with cross-functional teams (Data Engineers, Product Managers, Architects) to operationalize AI solutions.

- Build CI/CD pipelines for ML/GenAI workflows and support end-to-end MLOps practices.

- Leverage Azure and Databricks for training, serving, and monitoring AI models at scale.

Required Qualifications & Skills (Mandatory) :

- 4+ years of hands-on experience in AI/ML development, including Generative AI applications.

- Expertise in RAG, LLMs, and Agentic AI implementations.

- Strong knowledge of LangChain, LlamaIndex, or similar LLM orchestration frameworks.

- Proficient in Python and key ML/DL libraries : TensorFlow, PyTorch, Scikit-learn.

- Solid foundation in Deep Learning, Natural Language Processing (NLP), and Transformer-based architectures.

- Experience in building data ingestion, indexing, and retrieval pipelines for real-world enterprise scenarios.

- Hands-on experience with Azure cloud services and Databricks.

- Proven experience designing CI/CD pipelines and working with MLOps tools like MLflow, DVC, or Kubeflow.

Soft Skills :

- Strong problem-solving and critical thinking ability.

- Excellent communication skills, with the ability to explain complex AI concepts to non-technical stakeholders.

- Strong collaboration and teamwork in agile, cross-functional environments.

- Growth mindset with curiosity to explore and learn emerging technologies.

Preferred Qualifications :

- Familiarity with vector databases : FAISS, Pinecone, Weaviate.

- Experience with AutoGPT, CrewAI, or similar agent frameworks.

- Exposure to Azure OpenAI, Cognitive Search, or Databricks ML tools.

- Understanding of AI security, responsible AI, and model governance.

Key Relationships :

- Internal : Data Scientists, Data Engineers, DevOps Engineers, Product Managers, Solution Architects.

- External : AI/ML platform vendors, cloud service providers (Microsoft Azure), third-party data providers.

Role Dimensions :

- Contribute to AI strategy, architecture, and reusable AI components.

- Support multiple projects simultaneously in a fast-paced agile environment.

- Mentor junior engineers and contribute to best practices and standards.

Success Measures (KPIs) :

- % reduction in model development time using reusable pipelines.

- Successful deployment of GenAI/LLM features in production.

- Accuracy, latency, and relevance improvements in AI search and retrieval.

- Uptime and scalability of deployed AI models.

- Integration of responsible AI and compliance practices.

Competency Framework Alignment :

- Technical Excellence in AI/ML/GenAI

- Cloud Engineering & DevOps Enablement

- Innovation & Continuous Improvement

- Business Value Orientation

- Agile Execution & Ownership

- Cross-functional Collaboration