AI / ML Engineer

THE WORK: Explore new horizons with enthusiasm and curiosity. You will perform independently and become a subject matter expert while actively participating and contributing in team discussions. Your contributions will help provide thoughtful solutions to work-related challenges. This opportunity invites you to engage deeply with advanced Machine Learning, fostering growth and innovation. Join us in shaping the future with your expertise and passion. Responsibilities: Design and develop AI/ML and Generative AI solutions using Python Build and deploy applications leveraging Large Language Models (LLMs) Develop end-to-end pipelines including data ingestion, preprocessing, model integration, and deployment Implement prompt engineering and fine-tuning strategies for LLMs Integrate AI services into web/mobile/backend applications via APIs Work with vector databases and embeddings for semantic search and RAG architectures Optimize models and pipelines for performance, latency, and cost Collaborate with cross-functional teams to translate business requirements into AI solutions Ensure responsible AI practices including data privacy, bias mitigation, and explainability Monitor and improve model performance in production environments ________________________________________ Required Skills & Qualifications 6-8 years of experience in software engineering / AI / ML, Python roles, Strong programming expertise in Python Hands-on experience with ML/DL frameworks like PyTorch or TensorFlow Experience with LLM frameworks such as LangChain or LlamaIndex Solid understanding of NLP concepts and transformer-based models Experience with REST APIs and microservices architecture Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate) Experience with version control systems like Git ________________________________________ Preferred Qualifications Experience working with APIs from providers like OpenAI or open-source LLMs (Llama, Mistral) Knowledge of Retrieval-Augmented Generation (RAG) architectures Experience with model fine-tuning and evaluation techniques Exposure to cloud platforms (AWS / GCP) for deployment (excluding Azure) Understanding of containerization tools like Docker ________________________________________ Soft Skills Strong analytical and problem-solving skills Ability to translate complex AI concepts into practical solutions Good communication and stakeholder management skills Ability to work independently and in collaborative environments ________________________________________ Nice to Have Experience with AI agents / autonomous workflows Knowledge of MLOps practices and CI/CD for ML pipelines Exposure to multimodal AI (text, image, audio models) Experience with real-time AI applications (chatbots, voice bots, copilots)