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Muks Robotics

2.6

Generative AI Developer

India

Job Title: Generative AI Developer
Experience: 1-2 years
Company: Muks Robotics AI Pvt. Ltd.
Website: https://muksrobotics.com/
Location: Baner, Pune

About the Role:

We are looking for a passionate and skilled Generative AI Developer with 1-2 years of experience to join our team. The ideal candidate should have strong theoretical and practical knowledge of AI/ML, along with solid software development skills. You will be responsible for designing, developing, and deploying end-to-end AI solutions, including intelligent systems such as chatbots and multimodal applications.

Key Responsibilities:

  • Design, develop, and deploy machine learning and AI models for applications.
  • Build and maintain end-to-end AI pipelines (data collection → preprocessing → training → evaluation → deployment).
  • Develop intelligent systems such as chatbots, conversational AI, and multimodal systems.
  • Work with LLMs (Large Language Models) and VLMs (Vision-Language Models).
  • Implement and optimize audio processing pipelines including Speech-to-Text (STT) & Text-to-Speech (TTS).
  • Knowledge of Communication protocols (e.g.Websocket) and frameworks (e.g. FastAPI).
  • Collaborate with cross-functional teams to integrate AI solutions into robotic systems.
  • Write clean, scalable, and maintainable code following software engineering best practices.
  • Continuously research and apply new AI/ML techniques and tools.

Required Skills & Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field.
  • 1-2 years of hands-on experience in AI/ML development.
  • Strong understanding of Machine Learning, Deep Learning, and Generative AI concepts.
  • Proficiency in Python and experience with tools like PyTorch, LangChain, LangGraph, and Ollama.
  • Experience in building end-to-end Conversational AI systems and working with LLMs, VLMs, and multimodal models.
  • Knowledge of audio processing (STT/TTS), APIs, backend integration, and model deployment.

Good to Have:

  • Familiarity with Linux environments
  • Experience with Docker (containerization)
  • Basic understanding of AWS or cloud platforms

Work Location: In person

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