
Visionary AI Engineer
4 hours ago
We are seeking a seasoned expert to spearhead the development and deployment of cutting-edge AI/ML systems, with a strong focus on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and intelligent automation.
This role requires close collaboration with cross-functional teams to translate business needs into AI solutions, bringing expertise in building scalable ML infrastructure, deploying models in production, and staying at the forefront of AI innovation.
Key Responsibilities:- AI & ML System Development:
- Design, develop, and optimize end-to-end ML models using LLMs, transformer architectures, and custom RAG frameworks.
- Fine-tune and evaluate generative and NLP models for business-specific applications such as conversational flows, auto-replies, and intelligent routing.
- Lead prompt engineering and build autonomous AI agents capable of executing multi-step reasoning.
- Infrastructure, Deployment & MLOps:
- Architect and automate scalable training, validation, and deployment pipelines using tools like MLflow, SageMaker, or Vertex AI.
- Integrate ML models with APIs, databases (vector/graph), and production services ensuring performance, reliability, and traceability.
- Monitor model performance in real-time, and implement A/B testing, drift detection, and re-training pipelines.
- Data & Feature Engineering:
- Work with structured, unstructured, and semi-structured data (text, embeddings, chat history).
- Build and manage vector databases (e.g., Pinecone, Weaviate) and graph-based retrieval systems.
- Ensure high-quality data ingestion, feature pipelines, and scalable pre-processing workflows.
- Team Collaboration & Technical Leadership:
- Collaborate with product managers, software engineers, and stakeholders to align AI roadmaps with product goals.
- Mentor junior engineers and establish best practices in experimentation, reproducibility, and deployment.
- Stay updated on the latest in AI/ML (LLMs, diffusion models, multi-modal learning), and drive innovation in applied use cases.
- Bachelor's/Master's degree in Computer Science, Engineering, AI/ML, or a related field from a Tier 1 institution.
- 2+ years of experience building and deploying machine learning models in production.
- Expertise in Python and familiarity with frameworks like TensorFlow, PyTorch, Hugging Face, Scikit-learn.
- Hands-on experience with transformer models, LLMs, LangChain, LangGraph, OpenAI API, or similar.
- Deep knowledge of machine learning algorithms, model evaluation, hyperparameter tuning, and optimization.
- Experience working with cloud platforms (AWS, GCP, or Azure) and ML Ops tools (MLflow, Airflow, Kubernetes).
- Strong understanding of SQL, data engineering concepts, and working with large-scale datasets.
- Experience with prompt tuning, agentic AI systems, or multi-modal learning.
- Familiarity with vector search systems (e.g., Pinecone, FAISS, Milvus) and knowledge graphs.
- Contributions to open-source AI/ML projects or publications in AI journals/conferences.
- Experience in building conversational AI or smart assistants using WhatsApp or similar messaging APIs.
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