Provide technical guidance to customers adopting Google Cloud Platform services, troubleshooting technical problems, and delivering best practice recommendations.
Responsibilities
Provide solutions in cloud platforms and infrastructure; solve cloud platform tests.
Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
Work with customers to design and implement Cloud based architectures, migration approaches, and application optimizations that enable business goals.
Manage the customer’s problem through diagnosis, resolution, or investigation tools implementation to increase productivity for customer issues on GCP products.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Requirements
Bachelor's degree or equivalent practical experience
Nice to have: Experience with SQL database administration
Lead the design, architecture, and deployment of agentic AI systems for healthcare applications.
Compensation
The typical salary range for this role is $160,000 to $210,000 USD, depending on skills, qualifications, and relevant experience.
Responsibilities
Act as the technical authority for the Agentic AI roadmap, steering engineering pods from initial research prototyping through to production scale.
Design, build, and optimize scalable systems and orchestration pipelines capable of deep multi‑step reasoning, dynamic memory allocation, long‑context evaluation, and high‑fidelity tool utilization.
Bridge the gap between frontier machine learning research and enterprise software design, implementing state‑of‑the‑art techniques in post‑training fine‑tuning, preference alignment, and automated prompt optimization.
Architect and maintain multi‑dimensional quantitative evaluation frameworks and continuous testing infrastructure, including LLM‑as‑a‑judge rubrics and statistical tracking.
Develop and scale automated data curation pipelines to extract, filter, and structure user feedback signals, execution logs, and expert labels into ultra‑high‑quality training datasets for model fine‑tuning.
Requirements
Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent practical experience
Nice to have: Master’s degree or PhD in Computer Science, Artificial Intelligence, Machine Learning
Nice to have: 8+ years of industry experience specializing in advanced data structures, algorithms, distributed systems, and heavy‑duty scalable ML infrastructure
Nice to have: 3+ years of technical leadership experience
Nice to have: Research publications at top‑tier machine learning venues
Senior ML Engineer, Agentic AIEllipsis Health · San Francisco, US