Senior Manager, Machine Learning
Leads a technically hands-on Machine Learning team building foundational conversational AI platform capabilities and production-grade ML systems. The role requires 10+ years of applied ML or AI experience, team leadership, cloud expertise, and deep knowledge of LLM and MLOps technologies.
About the job
Responsibilities
- Collaborate with engineering and cross-functional teams to translate ambiguous business problems into a clear, prioritized ML product roadmap.
- Contribute hands-on technical expertise while providing strategic direction and mentorship to the team.
- Establish an engineering setup that enables rapid iteration, experimentation, and deployment of models.
- Improve team processes, tooling, and infrastructure for velocity, quality, and maintainability.
- Monitor the ML and AI landscape and promote strategic adoption of relevant research, techniques, and tools.
- Recruit, manage, and develop a diverse team of Machine Learning Engineers.
- Define and track KPIs measuring the impact and success of ML products.
- Manage project timelines, dependencies, and risks to ensure timely delivery of reliable, scalable ML solutions.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 10+ years of experience in Applied ML or AI, including 3+ years leading Machine Learning Engineers or data scientists.
- Experience defining and executing a multi-year technical vision for a large-scale ML platform or product.
- Expertise in designing, architecting, and deploying production-grade ML/AI systems.
- Knowledge of LLM orchestration, embedding models, and vector stores.
- Experience with MLOps and LLMOps patterns, including evaluation metrics for non-deterministic AI features at scale.
- Experience building cloud-based services using AWS, Google Cloud, or Azure.
- Experience managing high-volume data and data stores.
- Experience recruiting, hiring, and scaling high-performing ML or engineering teams.
- Strong communication, collaboration, mentoring, and cross-functional influence skills.
Nice-to-haves
- Master's or PhD in Computer Science, Machine Learning, Data Science, Statistics, or a related quantitative field.
- Publications at leading ML conferences or significant open-source contributions.
- Experience with conversational AI agents.
- Experience working in geographically distributed environments.
Compensation and Benefits
- Competitive pay, generous time off, parental and wellness leave, healthcare, retirement savings, and additional benefits.
- Benefits vary by location.
- Occasional travel may be required for project or team meetings.
Skills
Machine Learning, Artificial Intelligence, Llm Orchestration, Embedding Models, Vector Stores, MLOps, Llmops, AWS, GCP, Azure, Cloud Services, High-Volume Data, Data Stores, Conversational AI, Kpi Measurement
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