New opportunity

Technical Project Manager

General Robotics · Singapore

About this role

General Robotics is seeking a Technical Project Manager to lead the delivery of customer projects on the GRID platform. You will act as the primary point of contact between the company and customers, working hands-on with engineers to scope solutions, assess technical feasibility, and manage project tradeoffs. This role involves managing multiple Physical AI projects concurrently, from kickoff through deployment and handover. Responsibilities include breaking down customer requirements into technical scope and milestones, leading technical discussions with customer engineering teams, and shaping solution designs and model performance evaluation criteria. You will also serve as a bridge between customer feedback and the product roadmap. Required qualifications include a Bachelor's degree in a technical field, 3+ years of relevant project management experience, a working understanding of machine learning and robotics, and familiarity with the software development lifecycle. Preferred qualifications include a Master's degree, hands-on engineering experience, and familiarity with ROS, simulation platforms, or cloud APIs. The role requires the ability to travel to customer sites and the US office. Compensation is provided in the range of 100,000 SGD - 220,000 SGD.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Project ManagementTechnical Project ManagementMachine LearningRoboticsSoftware Development LifecycleGitJiraROSAirSimIsaac SimMujocoComputer VisionCloud PlatformsAPIsAgileScrum

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Part of your preparation guide is ready.

You can use the completed sections below while the rest is prepared.

Checking only loads saved content. It does not request a new AI analysis.

Understand the role

What matters most

Technical Scoping and Feasibility Assessment
You must translate high-level customer requirements into actionable technical milestones while assessing feasibility against the GRID platform's current capabilities. Success requires balancing customer expectations with engineering constraints to ensure realistic project delivery.
Cross-Functional Stakeholder Management
Acting as the primary bridge between customers and internal engineering/research teams in Singapore and the US is critical. You must maintain clear communication across technical and non-technical stakeholders to manage project risks and drive resolution.
Product Roadmap Influence
You are expected to synthesize field feedback and customer requirements into actionable insights for the GRID product roadmap. This requires a deep understanding of the platform's potential and the ability to identify new use cases for expansion.
End-to-End Project Lifecycle Execution
You will manage multiple concurrent Physical AI projects from kickoff through deployment and final handover. This involves defining success metrics, shaping solution designs, and ensuring model performance meets agreed-upon criteria.

Likely challenges to think through

Managing Technical Trade-offs in Physical AI
Physical AI projects often involve unpredictable hardware and sensor integration issues. Prepare by demonstrating how you have previously navigated technical trade-offs when a requested feature was not feasible or required significant custom engineering.
Distributed Team Coordination
The role requires working across time zones with US and Singapore teams. Prepare to discuss your strategies for maintaining alignment, managing blockers, and ensuring consistent project momentum in a fast-paced, distributed R&D environment.
Translating Complex AI Concepts
You must communicate technical details about robotics and machine learning to non-technical customer leadership. Prepare by practicing how you explain complex technical risks or performance metrics in a way that aligns with business objectives.

Practice your answers

Technical practice

Managing Physical AI Project Lifecycle

What to coverDescribe your approach to managing a robotics project from initial kickoff to final deployment. Focus on how you define technical milestones, manage hardware/software integration risks, and ensure the final handover meets customer acceptance criteria.

Assessing Technical Feasibility

What to coverHow do you evaluate whether a customer's specific request is feasible within the constraints of an existing platform like GRID? Discuss how you balance customer requirements against current system capabilities and when you would recommend a custom solution versus a standard feature.

Defining Model Performance Metrics

What to coverExplain how you collaborate with engineering teams to establish success metrics for AI model performance. Address how you translate business-level goals into technical evaluation criteria and data collection plans.

Bridging Customer Feedback to Product Roadmap

What to coverHow do you synthesize field feedback from multiple customer deployments into actionable insights for the product team? Suggestion: Focus on your process for prioritizing feature requests that provide the most value across the broader user base.

Technical Communication with Stakeholders

What to coverHow do you adapt your communication style when discussing complex robotics or AI integration issues with non-technical stakeholders versus customer engineering teams? Provide an example of how you ensure alignment on technical blockers.

Managing Distributed Engineering Collaboration

What to coverGiven the role involves working with teams in both Singapore and the US, how do you maintain visibility into technical progress and blockers across different time zones? Discuss tools or rituals you use to keep distributed teams synchronized.

Integration and Deployment Challenges

What to coverWhat are the common technical risks you anticipate when deploying AI models into physical environments, such as manufacturing or logistics? Discuss how you manage hardware, sensor, and environment-specific variables during the integration phase.

Simulation and Testing Workflows

What to coverHow do you leverage simulation platforms (e.g., Isaac Sim, AirSim, or Mujoco) to validate solution designs before physical deployment? Explain the role of simulation in reducing risk and accelerating the development lifecycle.

Behavioural practice

Handling Conflicting Project Priorities

What to coverDescribe a situation where you had to manage multiple concurrent projects with competing deadlines. Explain how you prioritized tasks, communicated delays to stakeholders, and ensured no project suffered from a lack of attention.

Driving Resolution on Technical Blockers

What to coverProvide an example of a time you identified a critical technical risk early in a project. Detail the steps you took to escalate the issue and how you facilitated a resolution between engineering and the customer.

Building Trusted Customer Relationships

What to coverShare an experience where you had to manage a difficult stakeholder or a challenging customer expectation. How did you build trust while maintaining the technical integrity of the project?

Adapting to a Fast-Paced R&D Environment

What to coverDescribe a time you worked in a high-growth or R&D-focused environment where requirements were constantly evolving. How did you maintain project structure and team focus amidst this ambiguity?

Sharpen your knowledge

Topics to prepare

Physical AI and Robotics Integration
The role focuses on deploying AI models onto physical hardware. Review the fundamentals of how AI models interact with robotic systems, specifically focusing on sensor integration, hardware constraints, and deployment environments. Exercise: Draft a hypothetical project plan for deploying a pre-trained vision model onto a robotic arm, identifying potential hardware-software integration risks.
Technical Project Lifecycle Management
You will manage projects from kickoff to handover. Review the software development lifecycle (SDLC) as it applies to robotics, including requirements gathering, feasibility assessment, and defining success metrics. Exercise: Create a template for a technical project kickoff document that includes sections for hardware requirements, model performance evaluation criteria, and stakeholder communication plans.

Skills to revise

Technical Feasibility Assessment
You must assess customer requests against the GRID platform's capabilities. Practice evaluating technical constraints by reviewing documentation for simulation platforms like Isaac Sim or AirSim. Exercise: Take a complex customer requirement (e.g., 'robot must navigate a dynamic warehouse floor') and break it down into technical milestones and potential blockers based on standard robotics capabilities.
Stakeholder Technical Communication
The role requires bridging the gap between customer needs and engineering execution. Practice translating high-level business goals into technical specifications. Exercise: Write a summary email to a non-technical stakeholder explaining a technical delay caused by a sensor calibration issue, focusing on the impact to the project timeline and the proposed mitigation strategy.
Project Tracking and Documentation
Familiarity with tools like Jira and Git is required to track progress and manage technical documentation. Exercise: Set up a sample Jira board structure for a robotics project, including columns for 'Hardware Setup', 'Model Training', 'Simulation Testing', and 'Deployment', and define the 'Definition of Done' for each stage.

Availability last checked: 18 Oct 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

KEEP EXPLORING

Similar AI jobs

Related skills and specializations in Singapore. Matched to this role, not your profile.

Explore more jobs

Finding similar opportunities…