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Staff Machine Learning Engineer (India, Remote)
Lead the development of foundational AI and machine learning capabilities for Twilio’s customer communications platform. Work across LLMs, personalization, real-time inference, and large-scale ML systems.
विवरण
- Develop core AI and machine learning capabilities for intelligent engagement experiences
- Create product functionality in a rapidly evolving, widely adopted environment
- Convert open-ended ideas into structured experiments and deliver results within weeks
- Research advanced LLM orchestration, retrieval methods, and data-driven personalization
- Engineer machine learning systems that operate at Twilio scale
- Expand technical expertise while delivering in a fast-paced environment
- Adopt modern AI development stacks to strengthen core product differentiation
- Lead research initiatives focused on contextual intelligence and large-scale machine learning challenges
आवश्यकताएँ
- At least 8 years of applied machine learning or AI experience, including end-to-end ownership of technically ambitious systems
- Ability to work from ambiguous requirements in zero-to-one environments with strong initiative
- Proficiency in Python
- Experience building cloud services on AWS, Google Cloud Platform, or Azure
- Experience handling high-volume data, streaming or real-time inference, and varied data stores
- Strong understanding of statistical machine learning, transformer architectures, and large language models
- Ability to elevate engineering standards through mentorship, design reviews, and technical guidance without formal management authority
- Clear communication and effective collaboration skills
- Preferred: experience developing autonomous agents for multi-turn conversations and persistent context
- Preferred: experience with user-behavior prediction, experiment design, and causal or counterfactual methods
- Preferred: experience collaborating in globally distributed teams
लाभ
- Competitive compensation
- Generous paid time off
- Substantial parental leave
- Wellness leave
- Healthcare coverage
- Retirement savings program
- Support for volunteering and charitable donations
- Remote-first working arrangement
- Occasional travel for project or team meetings
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