AI/ML Architect

Job description

REQUIREMENTS: Cloud AI services (AWS Sagemaker, Azure ML, GCP Vertex AI)Data engineering tools (Spark, Databricks, Airflow, Kafka)LLM architectures, fine-tuning, embeddings, vector stores (FAISS, Pinecone, Weaviate)MLOps tools (MLflow, Kubeflow, DVC, CI/CD pipelines) - 7+ years of experience in data science, machine learning, or AI engineering - 3+ years in a senior or principal-level architectural role - Strong proficiency in Python and common ML/AI frameworks (TensorFlow, PyTorch, Scikit-Learn, transformers libraries) Hands-on experience with: - Solid understanding of distributed computing, APIs, microservices, and containerization (Docker, Kubernetes). PERSONAL CHARACTERISTICS: - Strong communication skills and ability to translate complex technical concepts for non-technical audiences - Strategic mindset with experience influencing product and technical decisions - Ability to lead, mentor, and partner effectively across teams - Passion for innovation, experimentation, and continuous improvement RESPONSIBILITIES: - Architecture & Strategy - Design end-to-end AI/ML architectures, including data ingestion pipelines, feature stores, model training, deployment patterns, and monitori...