Джерело: CrawlJobs
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Senior Manager, Machine Learning

Stytch Індія ; Індія (вся країна)
Дистанційна робота

Дата публікації: 13.08.2026

This position is critical to leveraging Twilio’s massive data ecosystem and communication scale to build foundational platform capabilities for the next generation of conversational AI, specifically by owning the development of 0-to-1 platform features that empower developers to build sophisticated, context-aware customer engagement applications. This is a highly technical, hands-on role, requiring a 'player-coach' mentality to actively contribute technical expertise, bridge the gap between theoretical research and production-grade experimentation, and provide strategic direction to the team, rather than being purely a people manager. The leader in this role must demonstrate a strong bias for action, establishing a high-performing engineering setup that enables rapid iteration, experimentation, and deployment of models in this 0-to-1 setting. Furthermore, they will be responsible for working closely with cross-functional stakeholders to translate ambiguous business problems into a clear, prioritized product roadmap and communicate progress and updates to leadership.

Responsibilities

Collaborate with other engineering teams and cross functional teams to translate ambiguous business problems into a clear, prioritized ML product roadmap for your team; Have a 'player-coach' mentality, and contribute hands-on technical expertise while providing strategic direction and mentorship to the team; Establish a high-performing engineering setup that enables the team to rapidly iterate, experiment, and deploy models, fostering a culture of operational excellence and close partnership with product and business stakeholders; Drive continuous improvement in the team's processes, tooling, and infrastructure to optimize for velocity, quality, and maintainability; Actively monitor the ML and AI landscape to ensure the team is continuously up-to-speed on state-of-the-art research, techniques, and tools, promoting their strategic adoption where appropriate; Recruit, manage, and develop a diverse and highly-skilled team of Machine Learning Engineers, setting clear goals and expectations, and providing timely and actionable feedback; Define and track key performance indicators (KPIs) to measure the impact and success of the team’s ML products, communicating results clearly to leadership and stakeholders; Manage project timelines, dependencies, and risks, ensuring timely delivery of high-quality, reliable, and scalable ML solutions

Requirements

Bachelors in Computer Science, Engineering, or a related field; 10+ years of experience in Applied ML or AI, including 3+ years of either leading a team of Machine Learning Engineers or data scientists; Proven experience defining and executing a multi-year technical vision and strategy for a large-scale, complex ML platform or product; Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including deep knowledge of LLM orchestration, embedding models, and vector stores; Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics for non-deterministic AI features at scale; Strong background in building cloud-based services using AWS, GCP, or Azure, with experience managing high-volume data and various data stores; Experience in recruiting, hiring, and scaling high-performing Machine Learning or engineering teams; Exceptional communication and collaboration skills, with a proven ability to mentor engineers, influence product direction, and drive results across multiple teams

Nice to have

Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a closely related quantitative field from a top-tier university; A track record of relevant publications at top ML conferences or significant open-source contributions; Experience working on conversational AI agents; Experience working in a geographically distributed setting

Benefits

competitive pay; generous time off; ample parental and wellness leave; healthcare; retirement savings program; support for volunteering and donation efforts
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