Senior AI Engineer
Neemtree
- Experience
- 2+ yrs
- Location
- Bengaluru
- Job type
- Full-time
Required skills
- Artificial Intelligence
- Machine Learning
- Python
About the role
Key Responsibilities
1. Generative AI & Agent Development
- Design and build LLM-powered applications and AI agents
- Develop workflows using: LangChain / LangGraph / LlamaIndex
- Implement: Function calling / tool usage + Chain-of-Thought / ReAct reasoning
- Build end-to-end agentic systems capable of multi-step reasoning
2. RAG (Retrieval-Augmented Generation) Systems
- Design and implement scalable RAG pipelines
- Work with: Vector databases (Pinecone, FAISS, Milvus, etc.)
- Handle: Document chunking strategies
- Embedding generation and retrieval optimization
- Improve response quality and reduce hallucinations
3. LLM Optimization & Fine-Tuning
- Fine-tune models using: LoRA / PEFT techniques
- Optimize performance via: Quantization (8-bit / 4-bit)
- Manage: Context window limitations
- Prompt engineering strategies
- Work with alignment techniques like RLHF (understanding level expected)
4. Deep Learning & Model Understanding
- Strong grasp of: Neural networks & backpropagation
- Regularization techniques (Dropout)
- Experience with: LSTMs / RNNs (foundational understanding)
- CNNs (for vision-based use cases, if applicable)
- Train and optimize models using GPU/TPU environments
5. Machine Learning & MLOps
- Apply ML techniques for: Structured and unstructured data
- Strong understanding of: Class imbalance problems
- Evaluation metrics (Recall, Precision, etc.)
- Work with: XGBoost / Random Forest for tabular problems
- Handle: Model monitoring
- Data drift / concept drift detection
- Build production-ready ML pipelines
Required Skills & Experience
Must-Have
- 2–5 years of experience in AI / ML / GenAI engineering
- Strong hands-on experience with: Python + LLM frameworks (LangChain, LlamaIndex, etc.)
- Experience building: RAG pipelines + AI agents / tool-using systems
- Understanding of: Vector databases + Prompt engineering & hallucination mitigation
- Solid ML/DL fundamentals
Good to Have
- Experience with: Fine-tuning LLMs (LoRA/PEFT) + Quantization & optimization techniques + GPU-based model training
- Exposure to: MLOps tools & deployment pipelines + Real-time AI applications
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