Senior Manager, Machine Learning

Details

• 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.
• A 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.