AI Engineer

We are looking for an AI Engineer to design, build, and deploy machine learning models and data pipelines. 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 domainsDesign and architect data mining and synthetic labeling pipelinesPreprocess data, perform feature engineering and work with large-scale datasetsTrain and evaluate models using PyTorch or TensorFlowDeploy and monitor models using MLOps tools and cloud infrastructureUse Docker and container toolkit to train models in containerized environmentsCollaborate with backend and product teams to integrate AI capabilities into production systemsMaintain version-controlled, well-documented codebases Requirements 4+ years of experience in machine learning or AI engineeringStrong proficiency in Python and ML frameworks (PyTorch, TensorFlow)Solid understanding of ML fundamentals: supervised/unsupervised learning, deep learning, optimization, and evaluation metricsExperience 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 trainingVersion control with Git and collaborative development practicesProficiency in English language Good to Have Experience with vector databases (Qdrant, Weaviate, Pinecone)Knowledge of model quantization, distillation, or fine-tuning techniquesFamiliarity with Kubernetes for model serving at scaleExperience building synthetic data or annotation pipelines