Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Perform model validation and monitoring for ML systems: track performance, detect drift and data issues, conduct root-cause analysis, build and deploy models, write production code, and communicate findings to stakeholders.

Manage engineering teams delivering software components, ensuring project goals and product design alignment, while promoting Agile and DevOps principles.

Leads design, development, and maintenance of technical infrastructure for software delivery, focusing on cloud automation, CI/CD, and best practices in a hands-on expert capacity.

The Senior Software Engineer in Test (SDET) designs and implements test strategies, automation frameworks, and ensures quality for APIs, web, and mobile applications in a continuous integration environment.

Lead product strategy and delivery for fraud risk products. Build and align cross-functional teams, translate customer insights into product roadmaps, oversee technical requirements, ensure risk/security and regulatory compliance, and drive product revenue and execution.

Designs, implements, and optimizes secure, cost-effective AWS cloud infrastructure. Supports migrations to AWS, ensures compliance (PCI-DSS/SOC2/FFIEC), implements IaC with Terraform, observability, disaster recovery, and participates in on-call incident response.

Lead and build the Systems Reliability Engineering team, ensuring system reliability and efficiency while influencing company strategies and managing risks.

The Sr. Lead Product Manager will drive product vision and execution for digital assets, leading cross-functional teams to develop payment solutions, ensuring compliance and customer satisfaction.

Senior individual contributor providing enterprise-wide technical leadership: designs and codes large-scale, cloud-native distributed systems, drives architectural strategy and standards, leads multi-year initiatives, mentors senior engineers, ensures security, scalability, observability, CI/CD and regulatory compliance, and communicates risks and trade-offs to executives.

This role involves developing machine learning models, data science pipelines, and collaborating with teams to analyze and solve business problems using large datasets.