Chief Architect

1 week ago

udaipur, India beBeeMachine Full time

Key Position in AI EngineeringOur company is revolutionizing the way data paradoxes are solved by large enterprises.We're pioneering fully autonomous software operations, transforming the landscape of technology.About This OpportunityYou'll be responsible for architecting AI-driven autonomous systems that drive business value.As a senior member of the team, you will influence ML infrastructure, model deployment strategies, and data engineering decisions that align with our company's goals.What We OfferFreedom to Execute: Set your own goals, timelines, and approaches without bureaucratic hurdles.True Ownership: Significant equity packages ensure that your contributions have a direct impact on your compensation.Technical Challenge: Solve complex real-world problems with meaningful impact that drives innovation.Impact-Driven Culture: Directly influence product direction, company culture, and growth strategy.Exponential Upside Potential: Your equity stake grows with the company's success.RequirementsML ExpertisePassionate Builder: Proactive problem-solver who identifies, iterates, and ships solutions.ML Veteran: 5+ years building and deploying production ML systems at scale.Deep Learning Specialist: Hands-on experience with transformer architectures, LLMs, and generative AI.MLOps Mastery: Expert in ML pipeline orchestration, model monitoring, and A/B testing frameworks.Programming Excellence: Proficiency in Python, with experience in PyTorch/TensorFlow, and familiarity with systems languages (Go, Rust, C++).Technical Requirements:Enterprise AI: Experience deploying ML models in enterprise environments with strict SLAs.Autonomous Systems: Background in reinforcement learning, multi-agent systems, or autonomous decision-making.Data Engineering: Comfortable with large-scale data processing, feature engineering, and real-time inference.Cloud ML Platforms: Experience with AWS SageMaker, Google AI Platform, or Azure ML.Model Optimization: Knowledge of model compression, quantization, and edge deployment.

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