Primary Job Responsibilities:

• Own funnel outcomes: trial -> paid -> higher tiers
• Run growth experiments across the lifecycle
• Define KPIs and partner with BI to measure results
• Propose UX/UI adjustments through wireframes and best practices
• Collaborate with engineering and design to adjust flows and landing pages
• Evaluate and implement vendors/tools for growth optimization
• Monitor retention, churn, and ARPU metrics
• Translate data insights into action plans
• Ensure experiments align with business goals and revenue impact
• Participate in sprint planning as a key stakeholder
• Communicate impact and progress to leadership
• Balance rapid experimentation with long-term growth strategy

Position Summary:
Our partner is a technology company transforming traditional vehicles into autonomous systems for defense and industrial environments, and they are seeking a Sr/Staff AI Engineer to build the perception intelligence that makes those systems reliable outside controlled conditions. Your focus will center on developing multi-view computer vision and 3D perception systems that allow autonomous vehicles to understand complex environments. This role requires direct ownership of perception components from problem definition through deployment, not participation in isolated research or model experimentation. You will design, train, and deploy perception models that operate under noisy sensing, real-time constraints, and safety-critical conditions, working closely with robotics, autonomy, and systems teams to deliver capabilities that hold up in production.

Experience and Education:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
• Hands-on experience combining computer vision and machine learning in real-world systems
• Experience building multi-view or 3D perception systems for production applications
• Background in computer vision beyond single-camera detection or classification tasks
• Experience deploying machine learning models into production or safety-critical environments
• Experience in training and scaling models using GPU infrastructure and large datasets
• Exposure to real-time performance constraints, latency tuning, and system-level tradeoffs
• An advanced academic or research background is acceptable when paired with real-world system deployment
• Experience working with robotics, autonomy, vehicles, or other physical systems is strongly preferred

Skills and Strengths:

• Multi-view vision
• 3D computer vision
• Spatial reasoning
• Spatial geometry
• Depth estimation
• Camera calibration
• Scene alignment
• Computer vision
• Machine learning
• PyTorch
• TensorFlow
• Python
• C++
• Distributed training
• GPU-based training
• Large-scale datasets
• Real-time inference
• Performance optimization
• Model deployment
• Perception system architecture