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