Job Description & Requirements
We are seeking a Senior Member of Technical Staff – Machine Learning to drive the development of our core ML infrastructure and subsystems. In this role, you will lead end-to-end execution—from translating ambiguous requirements into practical designs to shipping scalable systems into production. This is a hands-on position requiring deep technical expertise and strong systems-level thinking.
Key Responsibilities
- Architect, deploy, and maintain core ML systems powering long-horizon AI features.
- Manage the full ML lifecycle, including data pipelines, model training, evaluation, inference, and continuous deployment.
- Convert experimental research models into resilient, production-ready microservices.
- Monitor, debug, and resolve complex production anomalies within strict latency, cost, and safety constraints.
- Work cross-functionally with Research, Product, and Platform teams to deliver user-facing value.
- Provide technical guidance, architectural oversight, and mentorship to junior and mid-level ML engineers.
Technologies: Python, PyTorch / JAX, Distributed GPU Training & Inference Workflows.
Qualifications
- Demonstrated experience shipping and sustaining production ML systems with active user bases.
- Strong mastery of production software engineering practices (modular design, testing, maintainability).
- Deep familiarity with modern deep learning models, optimization techniques, and edge-case behavior.
- Self-directed problem solver with excellent communication skills and an iterative approach to development.
Key Performance Indicators (KPIs)
- System Reliability: Production ML services consistently meet or exceed performance, latency, and reliability benchmarks.
- Operational Excellence: Fast resolution of production issues with minimal impact on service availability.
- Business Alignment: ML initiatives deliver measurable improvements to core product metrics and business objectives.
- Engineering Quality: Raised team standards through rigorous code reviews and impactful mentorship.