Machine Learning or AI Engineer

Roles & Responsibilities:

• Develop and deploy Python-based machine learning solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn, with specialized expertise in transformer-based architectures.
• Design, build, and optimize generative AI (GenAI) applications including text generation, summarization, code synthesis, and vector-based retrieval systems.
• Utilize GenAI orchestration frameworks like LangChain or LlamaIndex for multi-step generative workflows.
• Manage and integrate vector databases (e.g., Pinecone, Weaviate, Milvus) and embedding pipelines for semantic search and retrieval-augmented generation (RAG) systems.
• Process and manage large unstructured datasets using tools like Apache Spark for data preparation and LLM fine-tuning.
• Implement prompt engineering methodologies and develop reusable prompt templates and management systems.
• Work with cloud platforms (AWS, Azure, GCP) and GenAI model hubs/services (e.g., Hugging Face, OpenAI APIs, Anthropic).
• Diagnose and resolve technical issues related to inference latency, memory optimization, and cost efficiency for large foundation models.