Jobs at Path Robotics

Prospect and qualify potential customers through research, cold outreach, social media, and industry events. Nurture leads, maintain the sales pipeline, collaborate with Account Executives, support marketing campaigns, and communicate Path Robotics’ robotics and automation solutions. Provide prospect feedback and help improve sales strategies and pipeline quality.

Drive revenue growth across the Northeast territory by managing complex sales cycles from lead generation through close. Build strategic relationships with C-level stakeholders, understand manufacturing and robotics needs, tailor solutions, collaborate cross-functionally, provide market feedback to product teams, and mentor junior team members. The role uses the Challenger sales methodology and focuses on enterprise accounts and AI-driven robotic solutions.

Lead end-to-end deployment programs for robotic systems, from customer agreement and cell design through factory acceptance testing, customer-site installation, and transition to operations. Responsibilities include project planning, risk and issue management, stakeholder coordination, customer communication, technical problem-solving, status reporting, process improvement, and collaboration with engineering on new product introduction projects. Occasional customer-site travel is required.

Leads a Tier 2 software support team responsible for diagnosing complex production issues, managing escalations, driving root-cause analysis, and improving system reliability. Partners with Product, Systems Integration, Robotics, Engineering, and Customer Operations to deliver durable fixes. Establishes support processes, incident response practices, monitoring, alerting, documentation, and runbooks while mentoring engineers and building a customer-focused culture of continuous improvement.

The Machine Learning Engineer will develop and deploy AI systems for robotics, focusing on advanced manipulation techniques and control algorithms, collaborating across teams.

Architect and improve data platforms supporting machine learning, robotics, experimentation, model training, reporting, and business decisions. Build reliable Python and SQL pipelines for multimodal data, including sensor streams, telemetry, logs, and unstructured data. Monitor pipeline health, improve data quality and testing, establish governance and lineage standards, and enhance platform usability, performance, and tooling while collaborating with software, ML, robotics, and analytics teams.

Own enterprise sales for AI-powered robotic automation solutions, targeting major manufacturers. Responsibilities include territory and account planning, prospecting, multi-threaded stakeholder management, ROI and business-case development, negotiations, and closing complex multimillion-dollar deals through funded deployment. The role requires expertise in enterprise B2B sales, capital equipment or automation, Robotics-as-a-Service, and long sales cycles. Frequent customer-site travel, approximately 50%, is expected.

Drive revenue growth by managing complex enterprise sales cycles from lead generation through close. Build strategic relationships with C-level stakeholders, apply the Challenger sales methodology, uncover manufacturing customer needs, and position AI-driven robotic solutions. Collaborate with engineering, operations, product, and customer success teams to tailor solutions, provide market feedback, and support product innovation. Mentor junior team members as needed.

Own part templating quality, consistency, scheduling, and throughput for the Mission Control team. Responsibilities include creating process documentation, monitoring output, assigning and reprioritizing work, balancing team capacity against deadlines, onboarding and training team members, evaluating ramp-up performance, and coaching staff. The role combines hands-on templating with operational leadership and continuous process improvement.

As a Deployment Engineer, you will integrate and calibrate robotic systems, troubleshoot software issues, document errors, and train technicians.

The Senior Software Engineer will architect production-grade systems using Python, lead best engineering practices, build tools for research teams, design CI/CD workflows, and mentor peers in a collaborative environment.

This is an invitation to connect with the Talent Acquisition team at Path Robotics. Interested candidates can provide contact information and resumes for future opportunities.

Build and maintain front-end interfaces and supporting endpoints for a cloud and HMI platform using React/TypeScript and back-end services (Node.js/C#). Collaborate across teams, write tests, perform code reviews, deploy via CI/CD, and optimize reusable components and 3D visualizations for production manufacturing workflows.

The Machine Learning Engineer will build a robot-learning stack, design training infrastructure, deploy ML policies, and collaborate with engineers in heavy manufacturing.

As a Senior Machine Learning Engineer (Tech Lead), you'll lead the ML technical direction, design architectures for loco-manipulation, mentor team members, and manage cross-functional partnerships while writing production-quality code.

Lead architecture and hands-on development of robotics software across perception, planning, controls, and execution. Build scalable frameworks, motion planning, real-time control, kinematics, collision checking, SLAM, mapping, hardware interfaces, and integrate ML techniques. Mentor engineers, drive engineering best practices, and collaborate cross-functionally to deliver production robotic capabilities.

Manage post-sale customer relationships for North American manufacturing accounts, drive adoption and utilization of robotic systems, coordinate cross-functional teams, align production planning, act as the customer advocate internally, and enable account growth through ongoing support and expansion strategies.

Develop and maintain robotics software across perception, planning, control, and hardware drivers. Implement motion and trajectory planning, inverse kinematics, real-time control and feedback, localization and navigation for mobile platforms, and integrate sensors and cameras. Combine classical methods with learning-based approaches and operate software on Linux, ensuring reliability, testing, and deployment to live robotic cells.