Artificial Intelligence Engineer

Company Description zehnmind.ai specializes in designing and building custom AI systems tailored to specific business needs and challenges. The company focuses on applying advanced machine learning and pattern recognition techniques to create practical, scalable solutions. We are looking for an AI Engineer to design, build, and deploy machine learning models and data pipelines at zehnmind.ai. You will work across the full ML lifecycle — from data preparation and model training to deployment and monitoring. Key Responsibilities: -Develop and optimize models across LLMs, NLP, computer vision or related AI domains -Design and architect data mining and synthetic labeling pipelines -Preprocess data, perform feature engineering and work with large-scale datasets -Train and evaluate models using PyTorch or TensorFlow -Deploy and monitor models using MLOps tools and cloud infrastructure -Use Docker and container toolkit to train models in containerized environments -Collaborate with backend and product teams to integrate AI capabilities into production systems -Maintain version-controlled, well-documented codebases Requirements: -4+ years of experience in machine learning or AI engineering -Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow) -Solid understanding of ML fundamentals: supervised/unsupervised learning, deep learning, optimization, and evaluation metrics -Experience with MLOps tools (MLflow, Kubeflow, or SageMaker) -Familiarity with cloud platforms for model training and serving (AWS Lambda or similar) -Experience with Docker for containerized model training -Version control with Git and collaborative development practices -Proficiency in English language Good to Have: -Experience with vector databases (Qdrant, Weaviate, Pinecone) -Knowledge of model quantization, distillation, or fine-tuning techniques -Familiarity with Kubernetes for model serving at scale -Experience building synthetic data or annotation pipelines Please send your CV's to info@zehnmind.ai