Machine Learning Engineer

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

610 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.