Machine Learning Engineer
2 days ago
Role Overview
We are seeking a hands-on AI/ML Engineer with proven expertise in designing, building, and deploying intelligent chatbots. The ideal candidate will not only be technically strong but also capable of leading a small team of junior engineers, setting technical direction, and ensuring high-quality delivery.
Key Responsibilities
• Architect, design, and implement AI-driven chatbot solutions using state-of-the-art frameworks (e.g., Rasa, Dialogflow, LangChain, LLM APIs).
• Apply Natural Language Processing (NLP) and Machine Learning techniques for intent classification, entity recognition, and conversation management.
• Lead end-to-end chatbot development lifecycle – from data preparation and model training to deployment and monitoring.
• Guide junior engineers through code reviews, mentorship, and technical leadership.
• Collaborate with product, UX, and business teams to ensure chatbot solutions meet user and business requirements.
• Continuously evaluate and integrate new tools, frameworks, and AI advancements (e.g., LLM fine-tuning, vector databases, prompt engineering).
• Ensure production-grade performance, scalability, and security of deployed solutions.
Required Skills & Experience
• 6–10 years of professional experience in AI/ML and software engineering, with at least 3+ years building chatbot solutions.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Scikit-learn, spaCy, Hugging Face, etc.).
• Strong expertise in NLP techniques, conversational AI frameworks (Rasa, Dialogflow, Botpress, LangChain, etc.), and LLM APIs (OpenAI, Anthropic, etc.).
• Experience with cloud deployment (AWS/Azure/GCP) and containerization (Docker/Kubernetes).
• Knowledge of vector databases (Pinecone, Weaviate, FAISS, Milvus) for retrieval-augmented generation (RAG).
• Hands-on experience integrating chatbots with enterprise systems, APIs, and messaging platforms (Teams, Slack, WhatsApp, Web, etc.).
• Strong understanding of ML lifecycle management (MLOps), model deployment, monitoring, and retraining.
• Demonstrated ability to lead small technical teams and deliver projects in Agile environments.
Nice-to-Have
• Experience in Generative AI (LLMs, fine-tuning, prompt engineering).
• Background in analytics, recommendation systems, or voice-enabled bots.
• Open-source contributions or published work in chatbot/AI.
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