GenAI consultant

We are seeking a highly skilled and motivated GenAI Engineer to join our team and optimize our multimodal indexing pipeline. This role is critical to improving the performance and scalability of systems that process and index diverse data types including text, images, audio, and video for generative AI applications. Key Responsibilities Analyze and identify performance bottlenecks in the multimodal indexing pipeline. Design and implement scalable solutions to improve indexing throughput and latency. Collaborate with data scientists, ML engineers, and platform teams to integrate enhancements. Develop and maintain tools for monitoring and debugging pipeline performance. Ensure robustness and reliability of indexing across modalities. Document engineering solutions and contribute to technical knowledge base. Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or related field. 10+ years of experience in data engineering, ML infrastructure, or GenAI systems. Strong programming skills in Python, Java, or C++. Experience with multimodal data processing and indexing frameworks. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Understanding of transformer-based models and vector databases (e.g., FAISS, Milvus). Preferred Skills Experience with GenAI frameworks like LangChain, Hugging Face Transformers, or OpenAI APIs. Knowledge of distributed systems and real-time data pipelines. Prior work on optimizing large-scale ML workflows or retrieval-augmented generation (RAG). Career growth and learning opportunities.

Created: 2026-03-10