Perception Manager - Robotics & Drones (f/m/d)

, and continuous team development. You will work closely with autonomy, localization, safety, hardware, data, and product teams to ensure perception capabilities meet system-level performance, safety, and commercial requirements, and that Proofs of Concept mature into scalable, data-driven, production-ready perception stacks deployable across multiple robot platforms and customer deployments.

Your role:

Sensor & Perception Technical Leadership

• Own and drive the ML-centric perception strategy for AMR and drone platforms, spanning sensing, data pipelines, learned perception models, and runtime inference software.

• Lead teams responsible for:

  • Sensor data ingestion and preprocessing for learning-based systems (cameras, lidar, radar, depth, IMUs)
  • ML-based perception models, including object detection, tracking, segmentation, freespace, occupancy, and scene understanding
  • Learned or hybrid multi-sensor fusion approaches
  • Runtime perception inference, monitoring, and diagnostics

• Define perception KPIs and success metrics beyond raw accuracy, including latency, robustness, confidence calibration, generalization, and availability.

• Guide technical trade-offs between model complexity, latency, data requirements, compute cost, and robustness across diverse operating conditions.

Perception Team Management & Development

• Directly manage and grow multiple perception-focused engineering teams.

• Set clear expectations, goals, and priorities aligned with product roadmaps.

• Mentor engineers on:

  • ML system design for robotics (training-inference parity, domain shift, long-tail behavior)
  • Data-driven development, evaluation, and iteration
  • Scalable, production-oriented robotics software practicesFoster a strong engineering culture emphasizing quality, ownership, and continuous improvement.

• Foster a strong engineering culture emphasizing ownership, quality, empirical decision-making, and continuous learning.

• Support hiring, onboarding, performance reviews, and career development.

Sensor Integration & Platform Collaboration

• Partner closely with hardware and SoC teams to:

  • Evaluate and select sensors based on data quality and learning suitability, not just raw specifications
  • Define compute and acceleration strategies for ML inference (GPUs, NPUs, DSPs)
  • Ensure time synchronization, data transport, and bandwidth management appropriate for ML workloads

• Collaborate with platform, autonomy, and safety teams to define:

  • ML perception interfaces, data contracts, and confidence signals
  • Assumptions, limitations, and ML-specific failure modes
  • Integration points with localization, planning, and safety functions

• Support deployment of ML perception stacks across multiple robot form factors maximizing reuse.

Perception Quality, Robustness & Safety Alignment

• Ensure ML-driven perception systems perform reliably in real-world industrial environments (lighting variability, dust, weather, occlusions, dynamic obstacles).

• Collaborate with safety engineering to:

  • Identify ML-specific perception hazards and failure modes (misclassification, overconfidence, domain shift)
  • Support FMEAs, fault injection, and degraded-mode behaviors
  • Define runtime perception health monitoring, confidence assessment, and fallback strategies

• Drive continuous improvement through field data analysis, model retraining, and systematic iteration.

Data, Simulation & Tooling

• Define and own perception data strategy as a first-class responsibility, including:

  • Fleet and test-robot data collection strategies
  • Labeling workflows, automation, and tooling
  • Dataset curation, versioning, and coverage analysis
  • Performance evaluation and regression tracking across model versions

• Leverage simulation and scenario-based testing (Gazebo, Isaac Sim, Webots, or custom tools) for:

  • Synthetic data generation and domain randomization
  • Stress-testing ML perception under rare and adverse conditions

• Partner with DevOps and tooling teams to integrate MLOps practices into CI/CD, including model training, validation, deployment, rollback, and performance drift monitoring.

Customer & Partner Engagement

• Translate customer and use-case requirements into ML perception capabilities, data needs, and technical priorities.

• Support PoCs, pilots, and demos with customers and partners (AMR OEMs, drone OEMs, industrial automation vendors).

• Clearly communicate ML perception capabilities and limitations, including coverage assumptions and confidence characteristics.

• Contribute to build-vs-buy decisions for ML models, perception SDKs, sensors, and learning frameworks.

Your background:

• Bachelor's or Master's degree in Computer Science, Robotics, Electrical/Computer Engineering, or equivalent practical experience.

• 8+ years of robotics or embedded software experience, with 3-5+ years in technical leadership or people management.

• Hands-on experience delivering ML-based perception systems on real robotic platforms (AMRs, AGVs, drones, industrial robots).

• Strong background in learning-based perception, including several of:

  • Deep learning for vision and 3D perception
  • Multi-modal and multi-sensor learning
  • Object detection, tracking, segmentation, and scene understanding

• Experience deploying ML perception pipelines using ROS / ROS 2.

• Working knowledge of Linux-based systems and distributed middleware.

• Proven ability to lead teams shipping production ML systems, not just research prototypes.

• Strong communication and cross-functional collaboration skills.

• Experience deploying ML perception in industrial, logistics, or warehouse robotics environments.

• Experience managing ML perception systems for safety-relevant or human-adjacent robotics.

• Strong familiarity with ML data pipelines, training infrastructure, and model lifecycle management.

• Experience optimizing inference on GPUs, NPUs, or other accelerators under real-time constraints.

• Experience with large-scale perception datasets, labeling operations, and active learning.

• Experience using simulation for synthetic data generation and ML validation.

• Understanding of real-world ML perception challenges such as domain shift, data imbalance, and long-tail failure modes.

• Experience in startup or incubation environments with high ownership and ambiguity.

Traits we seek:

• Curiosity-driven problem solvers who investigate deeply and think systemically.

• Confident leaders who empower teams, set direction, and earn trust.

• Hands-on learners with an experimental, builder mindset.

• Resilient thinkers who see challenges as opportunities to learn and improve.

Aptiv Benefits:

• In addition to an attractive compensation package, Aptiv offers 30 days of vacation and overtime compensation

• A secure, permanent employment relationship awaits you with the opportunity to continually develop internally; also in an international environment

• Access to internal and external training, coaching and certifications allows you to continue your education

• We particularly recognize innovation and excellence

• A very international, collegial environment and collaboration with technical experts at eye level awaits you

• You have the opportunity to get involved in CSR activities

• At Aptiv you have the opportunity to actively shape the future of mobility in partnership with almost all global OEMs using state-of-the-art technology (e.g. e-mobility and autonomous driving).

Why join us?

• You can grow at Aptiv. Aptiv provides an inclusive work environment where all individuals can grow and develop, regardless of gender, ethnicity or beliefs

• You can have an impact. Safety is a core Aptiv value; we want a safer world for us and our children, one with: Zero fatalities, Zero injuries, Zero accidents

Apply today, and together let's change tomorrow!

#LI-UH1

Privacy Notice - Active Candidates: https://https://www.aptiv.com/privacy-notice-active-candidates

Aptiv is an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, gender identity, sexual orientation, disability status, protected veteran status or any other characteristic protected by law.