At least 6 years of experience as a Machine Learning or AI Engineer working with Python, JS/TS, Go, or similar languages. Comfortable working with frameworks such as PyTorch, TensorFlow or similar frameworks and ecosystems. Comfortable operating across cloud environments (AWS, GCP, Azure) and leveraging tools like Vertex AI, SageMaker, or Databricks. Proven ability to architect, build, train, and deploy production-grade AI models. Hands-on experience building or integrating AI-powered features (e.g., RAG, recommendation systems, semantic search, predictive analytics, etc.). Strong understanding of machine learning and neural network architecture, including data preprocessing, model evaluation, and serving at scale. Strong knowledge of MLOps/LLMOps best practices, including monitoring, CI/CD for ML, and production deployment. Experience building and maintaining scalable data infrastructure (e.g. data pipelines, feature stores, and data lakes). Strong understanding of software engineering fundamentals. Track record of translating complex AI concepts into practical client solutions, ideally in consulting or fast-moving environments. Proven experience working in a consulting or client-facing role with the ability to manage client expectations and timelines.