
Chief AI Architect
4 days ago
We are seeking an experienced AI developer to design and implement scalable, secure, and efficient cloud solutions to our AI initiatives.
The ideal candidate will have experience in NLP, predictive analysis, and other AI domains. They should also have exposure to CI/CD delivery pipeline, cost optimization, and cloud-native innovation.
Key Responsibilities:- Understand specific requirements including data ingestion from different services, analytics needs, and user-facing application features.
- Lead technical discussions with cross-functional teams to evaluate feasibility, define specifications, and assess performance and scalability for solutions.
- Define and design software architecture for integrating data pipelines, ML models, and full stack applications.
- Drive deployment of end-to-end solutions from data collection and ML model deployment to web access, with a focus on automation and resilience.
- Collaborate with cross-functional teams to design and deliver applications combining real-time data, machine learning, and cloud-native full stack platforms.
- Design, develop, and deploy scalable AI/ML models and systems to solve complex business problems across AWS and Azure.
- Optimize algorithms for performance, scalability, and accuracy.
- Evaluate and select appropriate AI tools, frameworks, and platforms.
- Work on data preprocessing and model evaluation.
- Ensure AI systems comply with standards.
- 6-8 years in AI/ML development.
- Hands-on expertise in AI/ML frameworks like TensorFlow, PyTorch, Keras or similar.
- Hands-on expertise in Python, Java or similar.
- Experience in cloud platforms AWS, Azure or similar for deploying AI models.
- Expertise in NLP, deep learning, and other AI domains.
- Understanding of data structures, algorithms, and software engineering principles.
- Excellent problem-solving and collaboration skills.
- Bachelor's or Master's degree in CS, IT, Engineering, or AI, Machine Learning, Data Science.
- Experience with MLOps and model deployment pipelines.
- Containerization (Docker, Kubernetes/EKS/AKS).
- Serverless architectures (Lambda/Functions).
- Experience working in Agile/Scrum environments.
- Experience with disaster recovery and enterprise-level high availability.
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