AI Innovator

2 days ago

Kurnool, Andhra Pradesh, India beBeeLeadership Full time ₹ 40,00,000 - ₹ 80,00,000

Lead AI Architect

The Role:

We are seeking a highly skilled and experienced AI Architect to join our team. As a Founding Senior Machine Learning Engineer, you will be instrumental in architecting our AI-driven autonomous systems, directly influencing our core ML infrastructure, model deployment strategies, and data engineering decisions.

Responsibilities:

  • Design and develop cutting-edge AI models for real-world problems.
  • Collaborate with cross-functional teams to integrate ML solutions into our product.
  • Develop and maintain high-quality, scalable, and efficient ML pipelines.
  • Conduct research and experiment with new techniques and technologies to improve our ML capabilities.

Requirements:

  • 5+ years of experience building and deploying production ML systems at scale.
  • Deep understanding of machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
  • Expertise in deep learning frameworks such as PyTorch or TensorFlow.
  • Strong programming skills in Python, with experience in PyTorch/TensorFlow.
  • Experience with cloud-based ML platforms such as AWS SageMaker, Google AI Platform, or Azure ML.

What We Offer:

  • Competitive equity package.
  • Opportunity to work on complex real-world problems with meaningful impact.
  • Collaborative environment with open communication channels.
  • Freedom to execute and innovate within the company.
  • Exponential upside potential through equity participation.

How to Apply:

  • Submit your profile, highlighting your relevant experience and skills.
  • Participate in Kaggle competitions or share recent ML projects, papers, or open-source contributions.

Our Promise:

  • Zero bureaucracy, allowing you to focus on innovation.
  • Transparent leadership with weekly strategy sessions.
  • Impact-driven culture where your voice shapes our product and strategy.
  • Significant equity package reflecting your early-stage commitment and risk.

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.

Why Choose Us?

Join us for the mission, freedom, opportunity to turn your boldest ideas into reality, and the chance to own a meaningful piece of the future we're building together.

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