Description

You will design, build, and deploy scalable machine learning and AI solutions for large-scale business problems.

This role is on-site.

Responsibilities

• Lead development of supervised, unsupervised, and deep learning models.
• Build and optimize data pipelines for training, validation, and inference.
• Productionize ML models using MLOps best practices including CI/CD, monitoring, and versioning.
• Collaborate with data engineers and product teams to integrate models into applications.
• Mentor junior engineers and communicate technical concepts to stakeholders.

Required Skills

• 12+ years of overall IT experience.
• Expert-level Python and SQL; exposure to Java or Scala is a plus.
• Deep experience with TensorFlow, PyTorch, Scikit-learn, and Keras.
• Strong knowledge of deep learning architectures: CNNs, RNNs, Transformers, and LLMs.
• Proficiency in data processing libraries: Pandas, NumPy, Spark, and Hadoop.
• Hands-on MLOps experience with MLflow, Kubeflow, Airflow, and model lifecycle management.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).

Preferred Skills

• Experience with Generative AI, LLM fine-tuning, and prompt engineering.
• Knowledge of NLP, Computer Vision, or Recommendation Systems.

Key Skills

Education

Any Graduate