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. You’ll 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

- Bachelor’s or Master’s 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, Sage Maker, 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.