AI Engineer

Eloelo is seeking a skilled AI Engineer for a permanent role in Bengaluru, India. This position offers a unique blend of research and production focus, challenging individuals to experiment with cutting-edge AI models and deploy them at scale. The AI Engineer will play a crucial role in shaping Eloelo's future AI infrastructure, contributing to systems that support global, real-time voice interactions.

Responsibilities

• Conduct research, fine-tune, and deploy Large Language Models (LLMs) for engaging conversational and interactive applications.
• Develop and enhance Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) systems.
• Construct robust voice-to-voice pipelines designed for minimal latency and maximum reliability.
• Explore and implement multimodal AI systems that integrate voice, text, and contextual data.
• Establish comprehensive evaluation frameworks to assess model quality, latency, and user experience.
• Optimize AI models for efficient real-time inference at a large scale.
• Collaborate effectively with backend, infrastructure, and product teams to integrate AI features into production environments.
• Maintain awareness of the latest advancements in AI research and apply them to practical use cases.

Requirements

• Possess 2-6 years of practical experience in AI/ML engineering or applied research.
• Demonstrate significant expertise with LLMs, including fine-tuning, prompt engineering, Retrieval Augmented Generation (RAG), and inference optimization.
• Have hands-on experience with speech technologies, encompassing Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and voice-to-voice pipelines.
• Exhibit strong programming proficiency in Python.
• Be experienced with deep learning frameworks such as PyTorch or TensorFlow.
• Show a solid understanding of neural networks, transformers, and sequence models.
• Have a proven track record of deploying models into production systems.
• Be familiar with cloud infrastructure, including AWS and GCP.
• Possess a strong problem-solving mindset and an experimental approach to development.
• Have experience with real-time or low-latency systems.
• Be exposed to multilingual speech models and streaming audio pipelines.
• Familiarity with MLOps practices, including model versioning, monitoring, and CI/CD.
• Ideal candidates may have contributions to research papers, open-source projects, or technical blogs.
• Experience in consumer-scale or real-time platforms is advantageous.