Top Tech Jobs & Startup Jobs

Conduct approximately 100 outbound cold calls daily, schedule and run product demos, and close real estate customers using a proven two-call sales process. This in-person Austin role offers sales coaching, professional growth, and performance-based earning potential. No prior experience is required; success depends on persistence, coachability, strong work ethic, and competitive drive.

Own customer retention by contacting unsubscribed customers, responding to low-quality ratings, collecting feedback, conducting winback efforts, and proactively addressing churn risks. Build automated, data-driven retention systems and maintain customer relationships through daily outreach. The role requires familiarity with real estate photography and HDR or flambient editing workflows, along with fluent English communication during US business hours.

Design, train, optimize, and deploy diffusion-based image editing and generative modeling systems. Build scalable training and high-performance inference pipelines, improve realism, consistency, controllability, and style fidelity, and ship model enhancements to user-facing AI image editing products. The role also contributes broadly across backend systems, internal tools, debugging, and AI workflows.

Handle inbound customer support for an AI real estate photo editing platform, resolving questions, quality issues, flagged shoots, human edit requests, and account problems. Identify and route bugs, churn risks, sales opportunities, and onboarding issues. Provide fast, clear, judgment-driven service while improving support workflows, scalability, and operational efficiency.

Edit short-form social videos and long-form YouTube content, handling cuts, transitions, motion graphics, sound design, color grading, and subtitles. Collaborate with the content team to follow creative briefs, repurpose recordings and interviews, meet tight deadlines, and provide creative input that improves engagement, retention, and brand consistency.

Build and improve AI image-editing systems, backend services, product features, training and inference pipelines, model-serving infrastructure, and media-processing workflows. Optimize computer-vision algorithms for speed and accuracy, develop internal tools, debug systems, and ship full-stack features for image editing, virtual staging, video workflows, and a model marketplace. The role requires broad engineering ability plus specialized expertise in areas such as computer vision, machine learning, frontend, or distributed systems.

Build, maintain, and optimize internal systems and AI-powered automations, including a company knowledge-base RAG system, affiliate tracking and payments, lead-to-sales workflows, customer support and CSAT tools, automated call analysis, dashboards, and HubSpot ticket creation. The role requires practical Next.js and Python knowledge, experience developing internal workflow tools, and familiarity with AI agents.

Edit short-form social videos and long-form YouTube content from raw footage through final post-production. Responsibilities include cutting, transitions, motion graphics, sound design, color grading, subtitles, repurposing interviews, and optimizing content for engagement and platform performance. Collaborate with the content team, follow creative briefs, meet tight deadlines, maintain consistent quality, and provide creative input on storytelling, pacing, hooks, and trends.

Build and ship AI image-editing products across the frontend, backend, and AI stack. Responsibilities include developing image-editing systems, backend services, training and inference pipelines, model-serving and media-processing workflows, computer-vision optimization, internal tools, debugging, and full-stack features for virtual staging, relighting, video editing, and a model marketplace. The role favors high-agency builders with broad engineering ability and specialized expertise in areas such as computer vision, machine learning, frontend, distributed systems, or media infrastructure.

Designs and operates scalable cloud infrastructure, distributed systems, AI training and inference platforms, backend services, media-processing pipelines, and CI/CD tooling. The role focuses on high-throughput production environments, GPU workload management, model serving, observability, incident response, and optimizing latency, reliability, and cost across user-facing AI products.