
5001 - 10000 employees
Millions of developers around the world have used Twilio to unlock the magic of communications to improve any human experience.Twilio has democratized communications channels like voice, text, chat, video, and email by virtualizing the world’s communications infrastructure through APIs that are simple enough for any developer to use, yet robust enough to power the world’s most demanding applications.By making communications a part of every software developer’s toolkit, Twilio is enabling innovators across every industry — from emerging leaders to the world’s largest organizations — to reinvent how companies engage with their customers.Founded in 2008, Twilio has over 5,000 employees in 26 offices in 17 countries and counting, with headquarters in San Francisco and other offices in Atlanta, Bangalore, Berlin, Bogotá, Denver, Dublin, Paris, Prague, Hong Kong, Irvine, London, Madrid, Munich, Malmö, Mountain View, Redwood City, New York City, São Paulo, Sydney, Melbourne, Singapore, Tallinn, and Tokyo.
🕒 May 14
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5001 - 10000 employees
Millions of developers around the world have used Twilio to unlock the magic of communications to improve any human experience.Twilio has democratized communications channels like voice, text, chat, video, and email by virtualizing the world’s communications infrastructure through APIs that are simple enough for any developer to use, yet robust enough to power the world’s most demanding applications.By making communications a part of every software developer’s toolkit, Twilio is enabling innovators across every industry — from emerging leaders to the world’s largest organizations — to reinvent how companies engage with their customers.Founded in 2008, Twilio has over 5,000 employees in 26 offices in 17 countries and counting, with headquarters in San Francisco and other offices in Atlanta, Bangalore, Berlin, Bogotá, Denver, Dublin, Paris, Prague, Hong Kong, Irvine, London, Madrid, Munich, Malmö, Mountain View, Redwood City, New York City, São Paulo, Sydney, Melbourne, Singapore, Tallinn, and Tokyo.
• 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.
• 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.
• Competitive pay • Generous time off • Ample parental leave • Wellness leave • Healthcare • Retirement savings program
Apply Now🕒 May 4
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