
Assistant Vice President
- Noida, Uttar Pradesh
- Permanent
- Full-time
- Define the technical roadmap for generative AI capabilities aligned with product and business goals.
- Design, develop, and deploy AI/ML models and solutions focused on US healthcare datasets.
- Design high‑level system architectures (model training pipelines, serving infrastructure, data ingestion, monitoring, and governance).
- Lead the development, fine‑tuning, and optimization of large language models (LLMs), diffusion models, multimodal transformers, and related architectures
- Architect solutions for distributed training (e.g., DeepSpeed, ZeRO, FSDP) and inference at scale (GPU/TPU clusters, Kubernetes, serverless).
- Implement observability, logging, and automated alerting for model performance, drift, and resource utilization.
- Incorporate security best practices: model encryption, secure inference, access control, and compliance with GDPR, CCPA, HIPAA, etc
- Develop prototypes and proofs-of-concept using generative AI models and tools to solve complex problems.
- Support the evaluation, selection, and integration of AI technologies and frameworks in the healthcare domain.
- Collaborate with data engineers and analysts to create dashboards, visualizations, and reports to communicate AI outcomes to business stakeholders.
- Monitor model performance and retrain models as needed to ensure accuracy and reliability in production environments.
- Mentor junior engineers and share best practices on AI development, cloud deployment, and healthcare data handling.
- Bachelor’s or higher degree in Computer Science, Engineering, Data Science, or a related technical field.
- 7+ years of experience designing and deploying AI/ML solutions
- Strong programming skills in Python, Scala, or similar languages used for AI development.
- Deep understanding of transformer architectures, attention mechanisms, and modern generative modeling techniques.
- Experience with generative AI models (e.g., GPT, BERT, or custom models) and machine learning frameworks like PyTorch, TensorFlow, or Hugging Face.
- Hands-on experience working with US healthcare data, including knowledge of healthcare standards (HL7, FHIR) and regulations (HIPAA).
- Experience with big data technologies (Spark, Delta Lake) and building data pipelines on Databricks.
- Proficient in SQL and data querying for healthcare datasets.
- Familiarity with cloud infrastructure, containerization (Docker, Kubernetes), and CI/CD pipelines for AI solutions.
- Strong analytical, problem-solving, and communication skills to work effectively with technical and non-technical stakeholders.