ob Summary:
We are seeking a highly skilled AI Applied Engineer to design develop and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable production-ready applications that deliver real-world business impact.
Key Responsibilities:
-
Design develop and deploy AI and Machine Learning (ML) solutions for digital transformation initiatives.
-
Collaborate with data scientists to operationalize AI models using MLOps best practices.
-
Integrate AI-driven components into existing enterprise systems and cloud platforms.
-
Build scalable data pipelines to support model training testing and deployment.
-
Leverage frameworks such as TensorFlow PyTorch or Scikit-learn for model development and optimization.
-
Work with cloud-based AI services (Azure AI AWS SageMaker Google Vertex AI etc.) for large-scale deployments.
-
Apply Natural Language Processing (NLP) Computer Vision and Predictive Analytics techniques to solve complex business challenges.
-
Partner with cross-functional teams to identify opportunities for AI automation and digital innovation.
-
Ensure solutions meet performance scalability and ethical AI standards.
-
Maintain detailed technical documentation conduct code reviews and mentor junior engineers.
Required Skills & Qualifications:
-
Strong programming skills in Python Java or C#.
-
Hands-on experience with AI/ML frameworks (TensorFlow PyTorch Keras Scikit-learn).
-
Experience deploying AI models into production environments.
-
Knowledge of MLOps tools (MLflow Kubeflow Airflow Docker Kubernetes).
-
Familiarity with data engineering tools and ETL pipelines.
-
Understanding of cloud platforms (Azure AWS or GCP) and their AI/ML services.
-
Proven experience in digital transformation or intelligent automation projects.
-
Strong analytical and problem-solving abilities with a focus on innovation.
-
Excellent collaboration and communication skills.
Nice to Have:
-
Experience in Generative AI (LLMs Prompt Engineering LangChain RAG frameworks).
-
Exposure to Edge AI IoT or Real-time analytics.
-
Familiarity with API integration and microservices architecture.
-
Knowledge of Responsible AI principles and model governance.
Education:
ob Summary: We are seeking a highly skilled AI Applied Engineer to design develop and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable production-ready applicat...
ob Summary:
We are seeking a highly skilled AI Applied Engineer to design develop and implement innovative digital solutions powered by Artificial Intelligence. The ideal candidate will bridge the gap between data science and engineering-transforming AI models into scalable production-ready applications that deliver real-world business impact.
Key Responsibilities:
-
Design develop and deploy AI and Machine Learning (ML) solutions for digital transformation initiatives.
-
Collaborate with data scientists to operationalize AI models using MLOps best practices.
-
Integrate AI-driven components into existing enterprise systems and cloud platforms.
-
Build scalable data pipelines to support model training testing and deployment.
-
Leverage frameworks such as TensorFlow PyTorch or Scikit-learn for model development and optimization.
-
Work with cloud-based AI services (Azure AI AWS SageMaker Google Vertex AI etc.) for large-scale deployments.
-
Apply Natural Language Processing (NLP) Computer Vision and Predictive Analytics techniques to solve complex business challenges.
-
Partner with cross-functional teams to identify opportunities for AI automation and digital innovation.
-
Ensure solutions meet performance scalability and ethical AI standards.
-
Maintain detailed technical documentation conduct code reviews and mentor junior engineers.
Required Skills & Qualifications:
-
Strong programming skills in Python Java or C#.
-
Hands-on experience with AI/ML frameworks (TensorFlow PyTorch Keras Scikit-learn).
-
Experience deploying AI models into production environments.
-
Knowledge of MLOps tools (MLflow Kubeflow Airflow Docker Kubernetes).
-
Familiarity with data engineering tools and ETL pipelines.
-
Understanding of cloud platforms (Azure AWS or GCP) and their AI/ML services.
-
Proven experience in digital transformation or intelligent automation projects.
-
Strong analytical and problem-solving abilities with a focus on innovation.
-
Excellent collaboration and communication skills.
Nice to Have:
-
Experience in Generative AI (LLMs Prompt Engineering LangChain RAG frameworks).
-
Exposure to Edge AI IoT or Real-time analytics.
-
Familiarity with API integration and microservices architecture.
-
Knowledge of Responsible AI principles and model governance.
Education:
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