Visionary Machine Learning Leader: Revolutionizing Autonomous Systems

3 days ago

Davangere, Karnataka, India beBeeInnovation Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Founding Sr. Machine Learning Engineer

Unlock Autonomous Innovation as a Founding Senior Machine Learning Engineer in a pioneering company.

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As an early-stage leader, you'll drive cutting-edge AI-driven solutions and directly influence core ML infrastructure, model deployment strategies, and data engineering decisions. With substantial equity ownership and freedom to execute, you'll have the opportunity to build something truly extraordinary and shape the future of autonomous systems.

This is your chance to turn research and ideas into reality, push the boundaries of innovation, and contribute meaningfully to solving complex real-world problems with significant impact.

Our collaborative environment offers:

  • Freedom to Execute: Set your own goals, timelines, and approaches without bureaucratic hurdles.
  • True Ownership: Founding engineers receive substantial equity packages, ensuring direct benefits from the value created.
  • Technical Challenge: Solve complex 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.

Our Ideal Candidate:

We're seeking:

  • Passionate Builders: Proactive problem-solvers who identify, iterate, and ship solutions.
  • ML Veterans: 5+ years building and deploying production ML systems at scale.
  • Deep Learning Specialists: 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++).

What We Offer:

  • Enterprise AI Experience: Deploy 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.

Are You Ready to Build Something Extraordinary?

If you're done optimizing ad algorithms or CRUD apps and eager to tackle genuinely impactful problems while building true ownership in a revolutionary company, we invite you to explore this opportunity further.

Accelerated Application Process for ML Engineers:

  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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