Virtusa
We are looking for an experienced Data Scientist with strong expertise in AI/ML, Generative AI, LLMs, NLP, and MLOps. The ideal candidate will lead solution design, predictive analytics, and time-series modeling initiatives while driving innovation in deep learning and enterprise AI deployments.
Key Responsibilities AI/ML & Generative AI Development
Design and implement advanced ML models, including LLMs and RAG-based NLP for enterprise applications.
Develop generative AI solutions for automation, personalization, and content generation.
Lead end-to-end AI solution design, ensuring scalability, security, and compliance.
Collaborate with stakeholders to align AI strategies with business objectives.
Predictive Analytics & Time Series Modeling
Build predictive models for forecasting and anomaly detection using time-series data.
Apply statistical and deep learning techniques for trend analysis and optimization.
Implement advanced DL architectures for image, text, and multimodal data.
Develop NLP pipelines for text classification, entity recognition, and conversational AI.
MLOps & Deployment
Establish robust MLOps frameworks for model lifecycle management, CI/CD, and monitoring.
Deploy AI models on cloud platforms (AWS, Azure) ensuring high availability and cost efficiency.
Leadership & Team Management
Lead cross-functional teams, mentor junior data scientists, and drive best practices in AI development.
Qualifications
Strong proficiency in Python, R, SQL, and ML/DL frameworks (TensorFlow, PyTorch).
Hands‑on experience with LLMs, Generative AI, NLP, and MLOps tools.
Expertise in time-series modeling, predictive analytics, and deep learning architectures.
Familiarity with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes).
Excellent communication and leadership skills.
Master or Ph.D. in Computer Science, Data Science, AI/ML, or related field.
Preferred Qualifications
Experience with AI governance and model validation frameworks.
Certifications in AWS/Azure AI services.
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Key Responsibilities AI/ML & Generative AI Development
Design and implement advanced ML models, including LLMs and RAG-based NLP for enterprise applications.
Develop generative AI solutions for automation, personalization, and content generation.
Lead end-to-end AI solution design, ensuring scalability, security, and compliance.
Collaborate with stakeholders to align AI strategies with business objectives.
Predictive Analytics & Time Series Modeling
Build predictive models for forecasting and anomaly detection using time-series data.
Apply statistical and deep learning techniques for trend analysis and optimization.
Implement advanced DL architectures for image, text, and multimodal data.
Develop NLP pipelines for text classification, entity recognition, and conversational AI.
MLOps & Deployment
Establish robust MLOps frameworks for model lifecycle management, CI/CD, and monitoring.
Deploy AI models on cloud platforms (AWS, Azure) ensuring high availability and cost efficiency.
Leadership & Team Management
Lead cross-functional teams, mentor junior data scientists, and drive best practices in AI development.
Qualifications
Strong proficiency in Python, R, SQL, and ML/DL frameworks (TensorFlow, PyTorch).
Hands‑on experience with LLMs, Generative AI, NLP, and MLOps tools.
Expertise in time-series modeling, predictive analytics, and deep learning architectures.
Familiarity with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes).
Excellent communication and leadership skills.
Master or Ph.D. in Computer Science, Data Science, AI/ML, or related field.
Preferred Qualifications
Experience with AI governance and model validation frameworks.
Certifications in AWS/Azure AI services.
#J-18808-Ljbffr