iLink Digital

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.