Data Scientist

5 days ago


nashik, India beBeeArtificialIntelligence Full time

Job Title: Senior Artificial Intelligence ArchitectAbout the RoleWe are seeking a highly skilled Senior Artificial Intelligence Architect to lead our machine learning pipeline development, leveraging modern cloud and MLOps practices to drive business growth.ResponsibilitiesPipeline Development: Design, build, and integrate Generative AI models (LLMs, Vision Models, Multimodal Models) into business applications, ensuring seamless integration with existing systems.AI Frameworks: Work with agentic AI frameworks to design autonomous and semi-autonomous AI agents, applying deep understanding of GenAI principles.Cross-Functional Collaboration: Collaborate with stakeholders to translate business needs into AI-driven solutions, driving strategic decision-making and business outcomes.Mentorship and Code Review: Review code, guide junior engineers, and ensure best practices in model development and deployment, promoting knowledge sharing and skills development.Innovation and Research: Evaluate new tools, frameworks, and approaches to keep the AI ecosystem cutting-edge, identifying opportunities for innovation and improvement.QualificationsExperience: 8–10 years of hands-on experience in Machine Learning, Deep Learning, and AI Engineering, with prior experience architecting AI/ML systems, including solution design, model lifecycle management, and scalability considerations.Skills: Strong expertise in Python, ML frameworks (TensorFlow / PyTorch), model training, optimization, and evaluation, data engineering concepts & ML pipeline automation, and deep understanding of GenAI principles.Required SkillsProgramming Languages: Proficiency in Python, strong understanding of ML frameworks (TensorFlow / PyTorch)Model Development: Experience in model training, optimization, and evaluationData Engineering: Knowledge of data engineering concepts & ML pipeline automationGenAI: Deep understanding of GenAI principles, including LLMs, prompt engineering, fine-tuning, embeddings, vector DBs, and RAGAgentic AI: Hands-on experience with agentic AI frameworks (LangChain, AutoGen, LlamaIndex, or similar)Cloud Experience: Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (SageMaker, Vertex AI, MLflow, Kubeflow, etc.)Bonus PointsStrong problem-solving abilities: Ability to convert business challenges into AI-based solutions


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