Doniyor Ashiraliyev

#ai #ml #middle AI Engineer Company: Zehnmind.ai Location: Tashkent (Office-based) Salary: $2,000+ USD (depending on skills and experience) 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: Model Development: Develop and optimize models across LLMs, NLP, CV, or related AI domains. Data Engineering: Design and architect data mining and synthetic labeling pipelines. Data Processing: Preprocess data, perform feature engineering, and work with large-scale datasets. Training & Evaluation: Train and evaluate models using PyTorch or TensorFlow. MLOps: Deploy and monitor models using MLOps tools and cloud infrastructure. Containerization: Use Docker and container toolkits to train models in containerized environments. Collaboration: Partner with backend and product teams to integrate AI capabilities into production. Code Quality: Maintain version-controlled, well-documented codebases. Requirements: Experience: 2+ years of commercial experience & 4+ years of total experience in ML/AI engineering. Language: Strong proficiency in Python and English. Frameworks: Deep understanding of PyTorch or TensorFlow. ML Fundamentals: Solid grasp of supervised/unsupervised learning, deep learning, optimization, and metrics. MLOps Tools: Experience with MLflow, Kubeflow, or SageMaker. Cloud & DevOps: Familiarity with cloud platforms (AWS Lambda or similar) and Docker for training. Git: Strong version control and collaborative development practices. 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. We Offer: Competitive salary starting from $2,000+ USD. Company-sponsored lunch. Comf… Read in full →