onsite
AI Engineer Manager - PricewaterhouseCoopers
AI Engineer
Lead a team of AI and data engineers to design, build, and deploy scalable data solutions using Python, Machine Learning, and cloud technologies such as AWS and Kubernetes.
About the role
Key Responsibilities
- Lead the architecture, development, and deployment of end‑to‑end AI and data pipelines that transform raw data into actionable insights.
- Mentor and manage a cross‑functional team of data scientists, ML engineers, and data engineers, fostering a culture of continuous improvement and innovation.
- Collaborate with stakeholders to define business requirements, translate them into technical specifications, and deliver production‑ready solutions on schedule.
- Ensure high availability, scalability, and security of data platforms by leveraging cloud services (AWS) and container orchestration (Kubernetes).
- Drive best practices in model governance, reproducibility, and performance monitoring across the AI lifecycle.
Requirements
- 10+ years of experience in data engineering, machine learning, or AI, with at least 3 years in a managerial role.
- Proficiency in Python, SQL, and modern ML frameworks (TensorFlow, PyTorch, Scikit‑learn).
- Hands‑on experience building data lakes, data warehouses, and deploying models to production using AWS services (S3, Redshift, SageMaker, EMR).
- Strong knowledge of containerization (Docker) and orchestration (Kubernetes) for scalable deployments.
- Excellent communication skills and a proven track record of delivering complex technical projects on time.
Skills
pythonmachine learningawskubernetes