<p><p></p><p></p><p><b>Requirements : </b><br/><br/>We are seeking a Senior AI Engineer with a strong foundation in machine learning, deep learning, and large-scale data processing.
The ideal candidate will lead the development and deployment of AI/ML models, drive innovation, and collaborate with cross-functional teams to create intelligent systems that solve real-world business problems.</p><br/><p><b>Key Responsibilities : </b><br/><br/>- Design, build, and deploy AI/ML models for use cases such as recommendation engines, NLP, computer vision, forecasting, and predictive analytics.<br/><br/></p><p>- Lead model experimentation, validation, and optimization efforts to ensure performance and accuracy.<br/><br/></p><p>- Develop and maintain MLOps pipelines for model versioning, deployment, and monitoring.<br/><br/></p><p>- Collaborate with data scientists, data engineers, and software developers to integrate models into production systems.<br/><br/></p><p>- Stay updated with the latest AI research and industry trends and translate them into actionable projects.<br/><br/></p><p>- Mentor junior engineers and contribute to AI best practices and coding standards.<br/><br/></p><p>- Ensure ethical AI usage, data privacy, and bias mitigation in models and datasets.</p><br/><p><b>Required Qualifications : </b><br/><br/>- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related field.
PhD is a plus.<br/><br/></p><p>- 5+ years of experience in AI/ML model development and deployment.<br/><br/></p><p>- Proficiency in Python and relevant libraries such as TensorFlow, PyTorch, scikit-learn, Hugging Face, etc.<br/><br/></p><p>- Strong knowledge of machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers), and data preprocessing techniques.<br/><br/></p><p>- Experience with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes).<br/><br/></p><p>- Familiarity with data pipelines, SQL/NoSQL, and scalable data platforms.<br/><br/></p><p>- Solid understanding of MLOps practices, CI/CD for ML, and tools like MLflow, Kubeflow, or SageMaker.</p><br/><p><b>Preferred Skills : </b><br/><br/>- Experience with LLMs and Generative AI (e.g., GPT, BERT, Stable Diffusion).<br/><br/></p><p>- Domain knowledge in [insert industry : e.g., healthcare, fintech, retail].<br/><br/></p><p>- Knowledge of Edge AI, reinforcement learning, or real-time inference systems.<br/><br/></p><p>- Contributions to open-source projects, patents, or AI publications.</p><p></p><p></p><br/></p> (ref:hirist.tech)