Machine Learning Engineer (RARR Job 5676)

1.            5+ years of hands-on experience in developing, fine-tuning, and deploying machine learning models.

2.            Strong proficiency in Python and PyTorch for building and optimizing deep learning models.

3.            Experience in LLM fine-tuning, prompt optimization, and task-specific adaptation.

4.            Hands-on knowledge of Graph Neural Networks (GNNs) for graph-structured and relational data.

5.            Expertise in anomaly detection using supervised and unsupervised learning techniques.

6.            Proven experience in developing and implementing risk scoring models and intelligent analytics frameworks.

7.            Ability to build and maintain Secure MLOps pipelines ensuring secure training, deployment, and model monitoring.

8.            Experience in managing model versioning, lifecycle tracking, and reproducibility using MLFlow or equivalent tools.

9.            Expertise in optimizing and deploying models for edge environments using ONNX Runtime, TensorFlow, or OpenVINO.

10.          Implement data privacy, model encryption, and robustness techniques for secure ML operations.

11.          Collaborate with cross-functional teams to ensure scalable, secure, and compliant ML solutions.

12.          Stay updated with the latest advancements in LLMs, GNNs, Secure MLOps, and Edge AI.

13.          Excellent problem-solving, analytical, and research skills.