Lead Data Scientist

The Role

As an AI/ML Architect, you will be responsible for designing, defining, and implementing the strategic AI/ML technology stack across enterprise-grade systems. Youll lead the development of scalable, secure, and production-ready AI solutions that power next-generation intelligent applications.

Key Responsibilities

• Design and oversee the architecture of large-scale AI/ML systems, including model lifecycle management, MLOps pipelines, and real-time inference platforms.
• Define AI/ML standards, best practices, and reusable components across teams and products.
• Lead the selection, evaluation, and integration of cutting-edge AI frameworks, models (including LLMs, multimodal systems), and tools.
• Architect secure, compliant, and scalable AI infrastructure with emphasis on performance, reliability, and observability.
• Champion responsible AI: ensure fairness, transparency, auditability, and ethical deployment of models.
• Mentor and upskill AI/ML engineers and data scientists on architecture principles and modern AI practices.

Qualifications

• Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a related field. PhD preferred.
• 8+ years of experience in AI/ML engineering, with at least 4 years in a lead or architectural role.
• Proven experience designing and deploying AI/ML systems in production environments (cloud-native, containerized, microservices).
• Expertise in deep learning, NLP, computer vision, reinforcement learning, and/or generative AI (LLMs, RAG, fine-tuning, agent systems).
• Strong hands-on experience with MLOps tools (e.g., Kubeflow, MLflow, SageMaker, Vertex AI, Airflow).
• Proficiency in cloud platforms (AWS, Azure, GCP) and infrastructure-as-code (Terraform, CDK).
• Experience with model monitoring, versioning, drift detection, and model governance.
• Excellent communication skills and the ability to translate technical concepts for non-technical stakeholders.