Experience: 12-15 years of professional experience in AI/ML, software engineering, or related fields, with at least 5 years in an AI architecture or leadership role.
Education: Bachelor s degree in computer science, Data Science, Engineering, or a related field. Master s or Ph.D. in AI, Machine Learning, or a related discipline is preferred.
Technical Skills:
Expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Open AI, Chat GPT and Prompt engineering
Proficiency in programming languages (e.g., Python, Java, C++).
Strong knowledge of cloud platforms (e.g., AWS, Azure, Google Cloud Platform) and their AI/ML services.
Experience with big data technologies (e.g., Hadoop, Spark, Kafka).
Familiarity with MLOps practices and tools (e.g., Kubeflow, MLflow, Docker, Kubernetes).
Understanding of database systems (e.g., SQL, NoSQL) and data engineering pipelines.
Preferred Qualifications
Certifications in cloud platforms (e.g., AWS Certified Machine Learning, Google Cloud Professional ML Engineer).
Experience with generative AI, reinforcement learning, or advanced NLP techniques.
Contributions to open-source AI projects or publications in AI/ML conferences/journals.
Familiarity with agile methodologies and DevOps practices