Senior Manager, Machine Learning

📋 Description

• Collaborate with various engineering and cross-functional teams to convert ambiguous business challenges into a clear and prioritized ML product roadmap for your team.

• Embrace a 'player-coach' approach by offering hands-on technical expertise while guiding the team through strategic direction and mentorship.

• Create a high-performing engineering environment that allows the team to quickly iterate, experiment, and deploy models, promoting a culture of operational excellence and strong partnerships with product and business stakeholders.

• Propel continuous enhancements in the team's processes, tools, and infrastructure to optimize for speed, quality, and maintainability.

• Keep a close watch on the ML and AI landscape to ensure the team remains informed about cutting-edge research, techniques, and tools, advocating for their strategic implementation when suitable.

• Recruit, manage, and nurture a diverse and highly-skilled team of Machine Learning Engineers, establishing clear goals and expectations, along with providing timely and actionable feedback.

• Define and monitor key performance indicators (KPIs) to evaluate the impact and success of the team’s ML products, clearly communicating results to leadership and stakeholders.

• Oversee project timelines, dependencies, and risks, ensuring the on-time delivery of high-quality, reliable, and scalable ML solutions.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related discipline.

• Over 10 years of experience in Applied ML or AI, including at least 3 years in a leadership role overseeing a team of Machine Learning Engineers or data scientists.

• Demonstrated experience in defining and executing a multi-year technical vision and strategy for a large-scale, complex ML platform or product.

• Profound expertise in designing, architecting, and deploying production-grade ML/AI systems, including in-depth knowledge of LLM orchestration, embedding models, and vector stores.

• Extensive experience with ML Ops and LLM Ops patterns, including the design and implementation of robust evaluation metrics for non-deterministic AI features at scale.

• Strong background in developing cloud-based services using AWS, GCP, or Azure, with experience in managing high-volume data and various data repositories.

• Proven experience in recruiting, hiring, and scaling high-performing Machine Learning or engineering teams.

• Exceptional communication and collaboration skills, with a track record of mentoring engineers, influencing product direction, and delivering results across multiple teams.

🏝️ Benefits

• Competitive pay

• Generous time off

• Ample parental leave

• Wellness leave

• Healthcare

• Retirement savings program