About the role
Requirements:
- Minimum of (3+) years of experience in AI-based application development.
- Experience fine-tuning large language models (LLMs) or working with domain-specific AI models.
- Experience building production-grade AI applications using RAG, AI agents, or multi-agent systems.
- Familiarity with Vector Search, Knowledge Graphs, and AI observability/evaluation frameworks.
- Experience deploying AI/ML solutions using Docker, Kubernetes, and cloud-native services.
- Contributions to open-source AI projects, research publications, or participation in AI communities are a plus.
- Proficiency in Python (libraries like NumPy, Pandas, Scikit-learn, and PyTorch/TensorFlow).
- Strong understanding of machine learning (ML) and deep learning (DL) algorithms.
- Hands-on experience with computer vision techniques (image classification, object detection, and segmentation).
- Practical experience with Generative AI and Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Claude, Gemini, or similar models.
- Experience building RAG (Retrieval-Augmented Generation) pipelines for enterprise applications.
- Hands-on experience building AI agents and agentic workflows using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, or similar orchestration frameworks.
- Familiarity with no-code / low-code AI automation platforms such as n8n, Dify, Flowise, or LangFlow.
- Hands-on experience with Vector Databases (Pinecone, Weaviate, ChromaDB, FAISS, or Qdrant)
- Experience with classification tasks and building predictive models.
- Proficiency with deep learning frameworks: PyTorch and/or TensorFlow / Keras.
- Exposure to NLP techniques or libraries (NLTK, Hugging Face, spaCy).
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Familiarity with MLOps practices and tools (Docker, MLflow, Git, CI/CD).
- Strong analytical and problem-solving abilities with a passion for solving real-world business challenges.
- Ability to translate business requirements into scalable AI and machine learning solutions.
- Excellent communication and collaboration skills for working with cross-functional teams and clients.
- Self-motivated learner with enthusiasm for exploring emerging AI technologies and industry trends.
- Ability to work independently while effectively managing priorities in a fast-paced environment.
- Strong ownership mindset with attention to quality, performance, and continuous improvement.