Senior Artificial Intelligence Engineer

2 weeks ago

Morādābād, Uttar Pradesh, India beBeeMachineLearning Full time ₹ 20,00,000 - ₹ 40,00,000

We're at the forefront of solving large enterprises' biggest data paradoxes and pioneering the world's first fully autonomous software operations.

About Our Role

You'll have the freedom to architect our AI-driven autonomous systems, directly influencing our core ML infrastructure, model deployment strategies, and data engineering decisions.

As a founding member of our company, you'll be instrumental in building substantial ownership by researching, experimenting, and deploying cutting-edge ML solutions.

  • Freedom to Execute: Set your own goals, timelines, and approaches without bureaucratic hurdles.
  • True Ownership: Founding engineers receive substantial equity packages (competitive with senior engineer salaries), 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.
What We're Looking For:
  • 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.

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