Artificial Intelligence/Machine Learning Engineer

Job Summary

Experience :

Location :

Key Responsibilities

• Architect and develop scalable and optimized AI-driven applications, focusing on robust system design and deployment.
• Integrate and leverage advanced AI capabilities using OpenAI APIs (e.g., GPT, DALLE, Whisper) to build intelligent and efficient product features.
• Utilize LangChain to design and implement robust AI agent frameworks that seamlessly connect with diverse tools, APIs, and external data systems.
• Develop and optimize high-performance RESTful APIs using Flask or FastAPI to efficiently serve and manage AI models and applications.
• Implement, fine-tune, and optimize Automatic Speech Recognition (ASR) functionalities using Whisper or similar state-of-the-art models.
• Proactively identify opportunities for system optimization, performance enhancement, and cost efficiency within AI products.
• Collaborate closely with product and engineering teams to translate complex business problems into actionable AI solutions and ensure successful, reliable deployment.
• Stay abreast of the latest advancements in AI/ML engineering, tools, and best practices to drive continuous improvement and innovation.
  

Required Skills And Qualifications

• M.Tech, B.Tech, or B.E in Computer Science, Information Technology, Artificial Intelligence, or a related engineering field.
• Demonstrated strong problem-solving abilities, logical reasoning, and a passion for fine-tuning and optimizing AI products for practical impact.
• Proven experience with LangChain for building LLM-powered applications and agentic workflows.
• Extensive experience integrating and working with OpenAI APIs (e.g., GPT, DALLE, Whisper).
• Hands-on experience with Whisper or similar ASR models.
• Proficiency in Python and developing scalable backend APIs using Flask or FastAPI.
• Fundamental understanding of Data Structures, Algorithms, and Object-Oriented Programming (OOPS) principles.
• Familiarity with foundational Machine Learning concepts, understanding of how models are trained, evaluated, and deployed.
  

Nice-to-have :