AI Engineer

• Design develop train evaluate and optimize machine learning and deep learning models.
• Perform feature engineering data preparation and dataset validation to improve model performance.
• Translate business and technical requirements into measurable machine learning objectives and success metrics.
• Conduct experiments benchmarking and model evaluations to validate and improve ML solutions.
• Develop modular and reusable Python pipelines for data preprocessing feature extraction model training and inference.
• Deploy machine learning models as scalable APIs or microservices with proper versioning and experiment tracking.
• Build and maintain automated training and inference workflows whilemonitoring model accuracy latency and drift in productionenvironments.
• Optimize model inference and data pipelines forperformance using CPU/GPU optimization techniques such as batchingmixed precision (FP16) and parallel processing.
• Containerize machine learning applications and implement CI/CD pipelines to support reliable deployments.
• Design and maintain ETL pipelines for processing structured and unstructured data including image audio and video datasets.
• Implement logging monitoring and alerting to ensure the reliability scalability and continuous improvement of ML services.
• Collaborate

Requirements

• Minimum 2 years of experience in AI Machine Learning or Deep Learning development.
• Strong knowledge of supervised and unsupervised learning deep learning and transfer learning techniques.
• Experience working with CNNs RNNs Transformers computer vision and multimodal AI models.
• Proficiency in Python programming and Bash scripting.
• Experience developing REST APIs using FastAPI or Flask.
• Hands-onexperience with PyTorch TensorFlow Scikit-learn NumPy PandasOpenCV Librosa Hugging Face OpenCLIP and TorchVision.
• Familiarity with Docker GitHub CI/CD pipelines MLflow Weights & Biases ONNX and TorchScript.
• Working knowledge of Linux environments SSH GPU utilization multiprocessing and basic AWS cloud services.
• Experience designing scalable machine learning systems and deploying production-ready ML microservices.
• Strong debugging troubleshooting and performance optimization skills.
• Ability to write clean maintainable and scalable code following software engineering best practices.
• Strong analytical problem-solving and experimentation skills.
• Excellent technical documentation communication and collaboration skills.
• Understandingof Agentic AI concepts including AI agents workflow orchestrationtool integration and autonomous task execution using modern LLMframeworks.
• Experience working directly with clients to understandbusiness requirements and translate them into practical scalable AI/MLsolutions.