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
