Principal Machine Learning Engineer

New
T
TwilioMachine learning
This role will be remote, and based in India - Karnataka, Tamil Nadu, Telangana State, Maharashtra and New Delhi.Full-TimePrincipal
Salary not disclosed
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Job Details

Experience
10+ years applied ML/AI experience
Required Skills
AWSPythonArtificial IntelligenceGCPMicrosoft Azure

Requirements

  • Bring 10+ years of applied ML/AI experience.
  • Show a track record of owning technically ambitious systems end to end.
  • Be comfortable working in a 0-to-1 setting with ambiguous requirements and a bias for action.
  • Be proficient in Python.
  • Have experience building cloud-based services on AWS, GCP, or Azure.
  • Have experience with high-volume data, streaming or real-time inference paths, and a range of data stores.
  • Have deep expertise designing, architecting, and deploying production-grade ML/AI systems.
  • Have experience with LLM orchestration, embedding models, and vector stores.
  • Have strong fundamentals in statistical machine learning algorithms, transformer models, and LLMs.
  • Be able to raise a team's technical bar through mentorship, design review, and standards without formal management authority.
  • Have strong communication skills and collaborate effectively with teammates.
  • Prior experience building autonomous agents that handle multi-turn conversations and maintain long-term context and consistency is desired.
  • A strong background in predictive modeling on user behavior, experiment design, and causal or counterfactual methods for partial randomization is desired.

Responsibilities

  • Build new functionality within a fast-moving product.
  • Turn ambiguous ideas into rigorous experiments and execute them within weeks.
  • Research state-of-the-art LLM orchestration, retrieval strategies, and data-driven personalization.
  • Build ML systems that operate at Twilio scale.
  • Acquire new technical skills and knowledge in a fast-paced, high-delivery environment.
  • Leverage and integrate AI development stacks to focus on core product differentiation.
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