AI Engineer: Driving Autonomous Software Operations

3 days ago

Vizag, Andhra Pradesh, India beBeeAI Full time ₹ 15,00,000 - ₹ 20,00,000

Transformative AI Pioneer

We're pioneering the world's first fully autonomous software operations. As an early-stage company driven by a meaningful mission, we seek exceptional engineering talent who values purpose, long-term impact, and significant equity ownership.

As a key architect of our AI-driven autonomous systems, you'll directly influence our core ML infrastructure, model deployment strategies, and data engineering decisions. You won't just be implementing models—you'll have the freedom to research, experiment, and deploy cutting-edge ML solutions while building substantial ownership in our company's future.

What Makes This Opportunity Unique:

  • Freedom to Execute: Set your own goals, timelines, and approaches without bureaucratic hurdles.
  • True Ownership: Founding engineers receive substantial equity packages, ensuring you directly benefit from the value you create.
  • Technical Challenge: Solve complex real-world problems with meaningful impact.
  • Impact-Driven Culture: Directly influence product direction, company culture, and growth strategy.
  • Transparent Leadership: Collaborative environment, weekly strategy sessions, and full visibility into company health and roadmap.
  • Exponential Upside Potential: Your equity stake grows with company success—potential for life-changing returns as we scale.

Key Requirements:

  • ML Expertise
    • Passionate 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++).
  • 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.

Accelerated Application Process for ML Engineers: To expedite your application and demonstrate your problem-solving skills, please complete one of the following:

  1. Kaggle Competition: Participate in any active Kaggle competition and share your results.
  2. Research Contribution: Share a recent ML project, paper, or open-source contribution you're proud of.

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