AI Engineer

* 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 while monitoring model accuracy, latency, and drift in production environments.
* Optimize model inference and data pipelines for performance using CPU/GPU optimization techniques such as batching,mixed 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-on experience with PyTorch, TensorFlow, Scikit-learn, NumPy, Pandas,OpenCV, 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.
* Understanding of Agentic AI concepts, including AI agents, workflow orchestration,tool integration, and autonomous task execution using modern LLMframeworks.
* Experience working directly with clients to understand business requirements and translate them into practical, scalable AI/ML solutions.