Top Tech Jobs & Startup Jobs

Help self-serve and corporate customers become successful, independent Roboflow users through technical onboarding, webinars, workshops, office hours, targeted enablement, and reusable educational content. Teach computer vision workflows including datasets, annotations, model training, evaluation, and deployment. Identify recurring customer friction, create scalable learning programs and documentation, monitor engagement, measure program effectiveness, and collaborate with Product, Support, Sales, and Field Engineering.

Lead and scale Roboflow’s SMB and Mid-Market sales organization. Responsibilities include managing and coaching Account Executives, owning revenue performance, improving pipeline generation and conversion, building repeatable sales processes, establishing forecast and operating cadences, hiring and developing sellers, and collaborating cross-functionally to refine segmentation, positioning, and go-to-market strategy.

Leads and scales Roboflow’s Sales Development organization, owning SDR team performance, pipeline generation, outbound strategy, account targeting, enablement, analytics, hiring, onboarding, and career development. Partners with Sales, Marketing, Revenue Operations, and Recruiting to build a scalable SDR operating system, improve opportunity quality and conversion, support technical buyer engagement, and establish a strong SDR-to-AE talent pipeline.

Build and manage Roboflow Labs’ frontier-lab business development pipeline. Own the full sales cycle, including outreach, discovery, evaluations, pricing, proposals, negotiation, procurement, legal coordination, and closing. Establish repeatable CRM, forecasting, pipeline-review, and account-planning systems while developing durable customer relationships. Represent Roboflow Labs at industry events and engage research scientists, human-data teams, technical executives, procurement, and legal stakeholders.

Conduct applied AI research focused on computer vision, multimodal, robotics, and coding models. Design datasets, evaluations, benchmarks, and reinforcement learning environments; analyze model failures; develop data remediation specifications; validate data quality through fine-tuning and ablation studies; contribute to open models; publish research; and collaborate with frontier labs to translate model roadmaps into data programs.

Build and own Roboflow Labs’ data platform, including catalog, delivery, contributor payout, and shared data infrastructure. Develop reliable pipelines for dataset ingestion, validation, packaging, provenance, rights tracking, and auditability. Automate quality controls such as consensus review, fraud detection, duplicate detection, and quality metrics. Establish engineering standards for architecture, observability, code review, releases, and on-call practices while partnering with operators and integrating with Roboflow’s core platform.

Own Roboflow Labs’ contributor supply-side growth, managing the funnel from awareness and application through onboarding, activation, retention, and reactivation. Build acquisition channels, referral programs, partnerships, and expert contributor cohorts. Set compensation benchmarks, optimize incentives, and protect network quality through screening, fraud prevention, identity verification, and contributor experience improvements.

Own end-to-end delivery of datasets and environments for leading AI labs, including intake, scoping, execution, quality review, and shipment. Build measurable quality processes, collaborate with researchers and engineers to shape data products, and manage capacity across contributor and reviewer networks. The role requires strong organization, judgment, communication, and practical experience with agents, evaluations, or reinforcement learning workflows.

Partner with sales to qualify opportunities and design scalable edge-based computer vision solutions. Translate customer needs into technical requirements, integrate hardware and software components, and advise on deployment, security, APIs, data handling, and model inference. Lead product demonstrations and proofs of concept, troubleshoot technical issues, and collaborate with Product and Engineering on customer feedback and improvements. The role requires strong communication, computer vision and machine learning knowledge, cloud and edge infrastructure experience, programming skills, and approximately 40% travel.

Build, secure, scale, and maintain cloud infrastructure supporting SaaS products, databases, storage, search, microservices, and machine-learning pipelines. Operate Kubernetes workloads, automate infrastructure with Terraform and Helm, improve reliability and observability, optimize costs, define SLOs and SLAs, participate in incident response and on-call rotations, address vulnerabilities, support customer security integrations, and maintain compliance with SOC 2, HIPAA, and GDPR requirements.