Senior Machine Learning Engineer: Revolutionizing Autonomous Software Operations

13 hours ago

Tirupati, Andhra Pradesh, India beBeeOpportunity Full time ₹ 40,00,000 - ₹ 90,00,000

We're on the cusp of a revolutionary era in autonomous systems, and we need exceptional talent to drive this vision forward.

Job Description

Our Mission:

At the forefront of innovation, our team is pioneering the development of fully autonomous software operations. We're not just building technology; we're shaping the future of data management and AI-driven decision-making.

What We Offer:

  • Equity-Driven Culture: Founding engineers receive substantial equity packages, ensuring they directly benefit from the value they create.
  • Freedom to Execute: Set your own goals, timelines, and approaches without bureaucratic hurdles.
  • Technical Challenge: Solve complex real-world problems with meaningful impact.
  • Impact-Driven Environment: Directly influence product direction, company culture, and growth strategy.
  • Transparent Leadership: Collaborative environment, weekly strategy sessions, and full visibility into company health and roadmap.

Compensation Structure:

  • Future Upside: Participation in all future funding rounds and liquidity events.

Required Skills and Qualifications:

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++).

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.

How to Apply:

Expedite your application by demonstrating your problem-solving skills through participation in an active Kaggle competition or sharing a recent ML project, paper, or open-source contribution you're proud of.

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