Top Tech Jobs & Startup Jobs

The Staff Machine Learning Engineer will develop and deploy advanced AI models and systems, enhance GenAI capabilities, and collaborate with cross-functional teams.

As a Staff Software Engineer focused on backend systems, you will design, implement, and operate micro-services, work with cloud technologies, and support large-scale distributed systems.

Lead design and implementation of an AI-native web platform, owning web framework, design system, CMS, CI/CD, infrastructure and SDLC agents. Define architecture, pioneer agentic workflows, set evaluation guardrails, mentor engineers, and drive cross-team technical alignment and migrations.

Lead customer-facing projects to design, build, and productionize end-to-end data and AI solutions on the Databricks platform. Own architecture, implement data pipelines, ML/AI integrations, and user-facing applications, train and empower customers, contribute reusable assets, and collaborate cross-functionally to ensure scalable, secure deployments and measurable outcomes.

Lead customer-facing, production-grade data and AI projects using Databricks: design architectures, build data pipelines, integrate ML/AI models, deliver applications, provide technical guidance, and create reusable assets to scale impact.

Lead Databricks-centric customer engagements delivering data engineering, data science, and cloud solutions. Design and deploy end-to-end data architectures, implement and optimize Apache Spark workloads, guide migrations, provide escalated operational support, manage technical project delivery, document/whiteboard solutions, and collaborate with stakeholders. Travel to customers ~20%.

Lead design for a 0-to-1 agent-driven AI product that makes Lakehouse data actionable. Define workflows, conduct user research, collaborate with PM and engineering, create intuitive visual and interaction designs, and mentor junior designers.

Customer-facing, hands-on engineer who architects and delivers production-grade data and AI solutions on Databricks. Responsibilities include end-to-end design, building data pipelines, ML/AI integration, deployment, stakeholder engagement, reusable assets creation, and guiding customers on architecture and adoption.

Own operational integrity of Databricks GovCloud secure enclaves: triage incidents, perform deep-dive debugging, run and adapt tooling/scripts inside air-gapped SCIF environments, unblock engineering pipelines, optimize patch deployment, and enforce compliance guardrails for multi-cloud data and Generative AI platforms.

Lead customer-facing projects to design, build, and productionize data and AI solutions on the Databricks platform. Own architecture, implement end-to-end data pipelines, ML/AI model integration, and user-facing applications. Collaborate cross-functionally, embed with customer teams, contribute reusable assets, and drive adoption while managing scope, timelines, and technical delivery.