Senior GenAI Engineer

Role Overview: As an AI & ML Engineer, you will be responsible for developing cutting-edge AI solutions and deploying end-to-end ML systems. You should have a strong background in Machine Learning, Deep Learning, Voice AI, Computer Vision, and cloud deployment. Your expertise in Python, ML frameworks, and collaboration will be crucial in building production-grade AI solutions. Key Responsibilities: - Build and optimize RAG-based chatbots using vector databases, hybrid retrieval, metadata filtering, and knowledge-base construction. - Fine-tune LLMs and integrate inference engines for scalable deployment. - Architect multilingual, domain-specific AI assistants for enterprise use cases. - Develop pipelines for web-scraping, document parsing, cleaning, and semantic retrieval. - Build multilingual voicebots leveraging various technologies and design low-latency real-time systems. - Train and deploy vision models for computer vision projects. - Develop prediction models, lead analytics projects, and handle data engineering and ETL pipelines. - Deploy AI systems on cloud platforms, monitor scalability, and lead Agile processes. - Mentor junior data scientists, own requirement mapping, and collaborate cross-functionally. Qualifications Required: - Core Technical Skills: Proficiency in Python, SQL, C++, NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, GBDT, ARIMA, Prophet. - LLM & GenAI Skills: Experience with GPT-4o, Qwen, Gemini, RAG, vLLM, ChromaDB, LangChain. - Voice AI Skills: Familiarity with Google STT/TTS, ElevenLabs, Sarvam. - Computer Vision Skills: Knowledge of YOLOv7/10, Mask R-CNN, OpenCV. - NLP Skills: Understanding of NLTK, Document Processing, OCR. - Deployment Skills: Experience with AWS, GCP, Azure, Containers, Edge Devices. - Tools: Proficiency in PySpark, Jira, GitHub/Bitbucket, Flask. - Soft Skills: Strong problem-solving mindset, excellent communication, ability to work in fast-paced environments. - Preferred Experience: Minimum 3 years in AI/ML, experience with enterprise chatbots or Voicebots, success in delivering automation initiatives. - Education: B.tech or related degree (Master's preferred), certifications in AI, ML, Python, SQL are a plus. Role Overview: As an AI & ML Engineer, you will be responsible for developing cutting-edge AI solutions and deploying end-to-end ML systems. You should have a strong background in Machine Learning, Deep Learning, Voice AI, Computer Vision, and cloud deployment. Your expertise in Python, ML frameworks, and collaboration will be crucial in building production-grade AI solutions. Key Responsibilities: - Build and optimize RAG-based chatbots using vector databases, hybrid retrieval, metadata filtering, and knowledge-base construction. - Fine-tune LLMs and integrate inference engines for scalable deployment. - Architect multilingual, domain-specific AI assistants for enterprise use cases. - Develop pipelines for web-scraping, document parsing, cleaning, and semantic retrieval. - Build multilingual voicebots leveraging various technologies and design low-latency real-time systems. - Train and deploy vision models for computer vision projects. - Develop prediction models, lead analytics projects, and handle data engineering and ETL pipelines. - Deploy AI systems on cloud platforms, monitor scalability, and lead Agile processes. - Mentor junior data scientists, own requirement mapping, and collaborate cross-functionally. Qualifications Required: - Core Technical Skills: Proficiency in Python, SQL, C++, NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, GBDT, ARIMA, Prophet. - LLM & GenAI Skills: Experience with GPT-4o, Qwen, Gemini, RAG, vLLM, ChromaDB, LangChain. - Voice AI Skills: Familiarity with Google STT/TTS, ElevenLabs, Sarvam. - Computer Vision Skills: Knowledge of YOLOv7/10, Mask R-CNN, OpenCV. - NLP Skills: Understanding of NLTK, Document Processing, OCR. - Deployment Skills: Experience with AWS, GCP, Azure, Containers, Edge Devices. - Tools: Proficiency in PySpark, Jira, GitHub/Bitbucket, Flask. - Soft Skills: Strong problem-solving mindset, excellent communication, ability to work in fast-paced environments. - Preferred Experience: Minimum 3 years in AI/ML, experience with enterprise chatbots or Voicebots, success in delivering automation initiatives. - Education: B.tech or related degree (Master's preferred), certifications in AI, ML, Python, SQL are a plus.