Description

You will design, architect, and oversee the implementation of end-to-end AI systems.

Responsibilities

• Design and architect agentic systems featuring memory, planning, and tool-use capabilities.
• Build hybrid AI architectures integrating Traditional ML, Deep Learning, and Generative AI.
• Develop applications using LLMs with frameworks like LangChain and Llamaindex.
• Architect RAG pipelines, prompt engineering workflows, and tool-using agents.
• Mentor junior data scientists and AI engineers across the Software Development Life Cycle.

Required Skills

• 8+ years of experience in AI/ML, including 3+ years in architecture or leadership.
• Proven delivery of production AI systems utilizing both Generative AI and traditional ML.
• Strong knowledge of LLMs, Transformer models, Vector embeddings, and Agent design.
• Proficiency in Python with libraries including TensorFlow, PyTorch, and SciKit-learn.
• Experience with cloud platforms such as AWS SageMaker, Azure ML, or GCP Vertex AI.
• Familiarity with ML deployment via MLOps tools like MLflow or Kubeflow.
• Experience applying XGBoost, SVM, and Random Forest models.
• Proficiency in SQL and developing mathematical formulations for business problems.

Preferred Skills

• PhD in AI, NLP, or Applied ML.
• Experience integrating AI into enterprise decision support tools.

Key Skills

Education

Any Graduate