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Own strategy, discovery, and delivery for a hardware product from concept through launch and support. Conduct market and customer research, define requirements, lead prototype testing, and collaborate with mechanical, electrical, firmware, design, and manufacturing teams to balance cost, performance, manufacturability, and schedule. The role focuses on robotics products, iterative physical testing, and delivering reliable industrial hardware.

Serves as the first technical contact for inbound prospects, qualifying leads, conducting discovery calls, documenting CRM activity, and routing opportunities to sales or engineering teams. Provides initial technical guidance on robotic capabilities, system requirements, and deployment scenarios; supports demos, sales collateral, lead handoffs, and response-time SLAs. Collaborates with marketing to improve lead quality and funnel performance while maintaining knowledge of robotics, automation, and hardware/software integrations.

Own the full B2B sales cycle for industrial robotics across a Texas territory, including prospecting, discovery, technical demonstrations, proposals, negotiation, and closing. Build relationships with manufacturers, logistics companies, and industrial customers; translate operational needs into robotics solutions and business cases; maintain CRM pipeline data; coordinate integration efforts; and drive repeat business, expansions, and referrals.

Staff Forward Deployed Engineer embedded with a major robotics customer, responsible for debugging and improving realtime robot-control systems, SDKs, APIs, ROS 2 integrations, and robot controllers. The role combines customer technical leadership, production incident resolution, software delivery, reliability engineering, and platform generalization. It requires extensive onsite work in the San Francisco Bay Area, with recurring travel to New York.

Design and own automated test suites and hardware-in-the-loop infrastructure for controls and industrial integration. Exercise industrial protocols (Modbus, EtherNet/IP, EtherCAT, PROFINET), build PLC/protocol simulators and safety-system validation, and collaborate with software and applications engineers to validate integrations in real time. Deliver maintainable test code, fixtures, and reviews for protocol compliance and CI/CD pipelines.

Build and own AI team systems spanning data ingestion, labeling, training and evaluation infrastructure, model deployment, perception integration, and customer-facing applications and APIs. Drive high-impact technical projects, make hands-on architectural decisions, mentor engineers, and support a broad AI software stack. The role is approximately 70% backend and 30% frontend, with focus areas including ML Ops, data pipelines, or computer vision.

Execute manual regression, smoke, exploratory, and release-candidate testing across robot control software, teach pendants, core workflows, and physical six-axis robots. Create and maintain test cases in Qase, document reproducible defects with logs and build details, collaborate with SDETs and systems test engineers, identify coverage gaps, and perform basic hardware recovery such as re-homing and resets.

Corporate Controller responsible for building and scaling the accounting function, owning monthly, quarterly, and annual close, implementing COSO and SOX-caliber controls, leading PCAOB external audits, and managing technical accounting under US GAAP. The role includes SEC reporting readiness, equity administration, ERP implementation, inventory accounting, policy development, team building, and IPO preparation. This hybrid position partners closely with finance leadership, the board, audit committee, and manufacturing operations.

Develop and optimize advanced AI models, training pipelines, evaluation frameworks, and debugging systems for robotics applications. Lead rapid experimentation, model architecture development, fine-tuning, performance optimization, and interpretability efforts. Collaborate with engineering teams on training infrastructure and deployment. The role emphasizes ML planning for autonomous vehicles, diffusion and autoregressive models, reinforcement learning, and translating research into production systems.

Develop and optimize AI models and training systems for robotics applications, focusing on design, implementation, and performance optimization of ML models.