Senior Data Scientist - NLP / Deep Learning

Key Responsibilities :

• Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems.
• Lead projects involving natural language processing (NLP), including fine-tuning transformer-based models for tasks such as classification, summarization, and generation.
• Manage the entire ML lifecycle including data preparation, model training, evaluation, optimization, deployment, and monitoring.
• Implement MLOps practices using tools like MLflow or Kubeflow to enable reproducibility, scalability, and automation of ML pipelines.
• Collaborate with cross-functional teams including data engineers, product managers, and software developers to productionize models.
• Utilize cloud platforms (AWS, GCP, Azure) and ML services (e.g., SageMaker, Vertex AI) for scalable model training and deployment.
• Apply best practices for model optimization techniques such as quantization and pruning to enhance performance.
• Integrate ML solutions into containerized environments using Docker, Kubernetes, and CI / CD pipelines.
• Work with distributed computing frameworks (e.g., Apache Spark, Ray) for handling large datasets efficiently.
• Explore and implement vector databases like FAISS or Milvus for similarity search and retrieval-based AI systems.
• Continuously monitor model performance, implement drift detection, and conduct hyperparameter tuning for model stability and accuracy.
• Stay up to date with the latest advancements in AI / ML and proactively introduce improvements into the data science stack.

Required Skill Set :

Proficiency in :

In-depth knowledge and hands-on experience in :

Preferred Qualifications :

(ref : hirist.tech)