About the job
Job Purpose
Join Tarjama as a Senior AI Engineer, where you will lead the design, development, and implementation of cutting-edge AI systems that enhance our language, document, and speech intelligence capabilities across various products. Your expertise will transform intricate business and product requirements into robust, scalable AI solutions, while ensuring their reliability and continuously improving their performance, accuracy, and cost-effectiveness.
In this pivotal role, you will help define Tarjama's AI architecture and establish best practices, working collaboratively with product, engineering, and data teams to deliver impactful AI applications that elevate our localization, content, and technology solutions.
Duties & Responsibilities
Multimodal AI Development
- Create and integrate text-based AI systems, including LLM pipelines, embeddings, rerankers, and scalable RAG architectures.
- Develop and enhance document understanding systems utilizing OCR, layout-aware vision models, and multimodal reasoning.
- Design speech-based AI solutions, such as STT, TTS, and conversational voice agents.
- Establish multilingual and translation pipelines, ensuring high quality, low latency, and scalability across various languages.
AI Product Development & Deployment
- Lead the development of AI-powered features from conception to production, ensuring alignment with product and business objectives.
- Deploy, monitor, and optimize AI systems in production environments, ensuring their reliability, scalability, and cost-effectiveness.
- Work closely with software engineering teams to integrate AI components into secure, maintainable, and scalable architectures.
- Implement observability, logging, and monitoring to support ongoing improvement of AI systems.
Model Evaluation & Optimization
- Develop evaluation strategies and metrics for multimodal AI systems, focusing on accuracy, latency, robustness, and user impact.
- Benchmark, fine-tune, and optimize models to enhance inference performance, cost-effectiveness, and scalability.
- Conduct experiments and A/B testing to validate model and system enhancements.
- Identify and address model failure modes, biases, and performance regressions.
AI Agentic Workflows & Frameworks
- Design, implement, and maintain AI-driven workflows that coordinate language, vision, and speech models to tackle complex, real-world tasks.
- Build and enhance task-oriented, tool-using AI agents leveraging modern agent frameworks and orchestration patterns.
