Agentic-AI | Machine Learning Architect
2 days ago
Company Description
AI-Data Value Info Com-Tech Alliance is a strategic advisory collective specializing in Advanced AI Engineering, Data Protection, Cyber Law, and Global Tech Compliance. With deep expertise in Generative AI frameworks like LangChain, RAG, and PyTorch, we guide technology ventures to ensure secure, transparent, and compliant scaling across global markets. We integrate legal and security protocols into the technology lifecycle and operational processes. With over 10 years of specialized experience, the Alliance addresses complex challenges in Technology Law, Corporate Cyber Crime, and Digital Fraud Defense. Our mission is to empower AI-driven businesses to thrive in an ever-evolving digital landscape.
Role Description
We are seeking a full-time Machine Learning Architect for our on-site office in Gurugram. This role will involve designing and implementing machine learning architecture to support AI innovation. Responsibilities include developing scalable machine learning solutions, creating robust software architectures, and applying best practices in programming and software design patterns. The Machine Learning Architect will collaborate with cross-disciplinary teams to align technical solutions with regulatory and business goals, ensuring full compliance with global standards and data protection laws.
Qualifications
- Expertise in Software Architecture, Design, and Development
- Proficiency in Programming and knowledge of Design Patterns
- Strong skills in Software Development and implementation of scalable technologies
- Proven experience in developing and optimizing software solutions for AI applications
- Understanding of Generative AI frameworks is an advantage
- Experience working with global regulatory and compliance standards in technology is a plus
- Strong analytical skills and the ability to work collaboratively within cross-functional teams
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or a related field
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