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About the role
Position Principal Architect AI/ML Department: Engineering & Technology | Function: AI/ML Platform Engineering Min Exp 12+ yrs Max salary up to 40 lpa Required Education & Certifications - Bachelors or Masters degree in Computer Science, Engineering, Mathematics, or a relatedtechnical field. - Certifications in cloud platforms (AWS, Azure, GCP) or specialized AI/ML credentials are preferred Responsibilities AI/ML Architecture & Engineering Hands-on Development & Technical Leadership AI/ML & GenAI Solution Development MLOps & Platform Engineering Cloud & Distributed Systems Data & Platform Readiness Technical Mentorship & Collaboration Work Experience - 12+ years of experience in AI/ML, software engineering, or platform engineering roles. - Proven experience designing and deploying AI/ML solutions in production environments. - Solid hands-on expertise in Python, SQL, and distributed computing frameworks. - Hands-on experience with ML libraries/frameworks (TensorFlow, PyTorch, Scikit-learn). - Experience building end-to-end ML systems not just modelling. - Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI, Airflow). - Hands-on experience with GenAI/LLMs (RAG, embeddings, fine-tuning, prompt engineering). - Experience working with cloud platforms (AWS/Azure/GCP). Key Skills & Competencies Technical Skills - Deep expertise in AI/ML architecture, distributed systems, and cloud-native engineering. - Strong knowledge of system design, scalable architectures, data pipelines, and distributed systems. - Proficiency in Python, SQL, TensorFlow, PyTorch, and Scikit-learn. - Experience with MLOps platforms and CI/CD-integrated ML workflows. - Familiarity with vector databases, knowledge graphs, or multimodal AI systems is a plus. - Exposure to real-time ML systems or streaming architectures is a plus. - AI & Digital Competencies - Hands-on experience with GenAI and LLM-based solutions including RAG, embeddings, and - fine-tuning. - Experience building AI platforms or internal ML frameworks. - Strong understanding of AI adoption, model lifecycle management, and intelligent - automation. - Leadership & Behavioural Competencies - Strong hands-on technical mindset with a passion for building scalable, production-grade - systems. - Ability to operate as a player-coach architect and active contributor simultaneously. - Deep problem-solving skills with a focus on scalability and performance. - Strong collaboration and stakeholder management skills across engineering, product, and - platform teams. - Continuous learning mindset, especially in emerging AI and GenAI technologies. Please call Hemant 9715166618 for more info Regards Hemant 9715166618 .
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