Job Description:

Job Description: Senior AI/ML Engineer with Robotics Specialization

Location: Singapore (Hybrid Work Model)

Role Level: Senior / Senior Specialist (Individual Contributor with technical leadership)

Role Summary

We are looking for a Senior AI/ML Engineer with Robotics specialization to design and deploy Physical AI solutions—AI models and robotics software that perceive, plan, and act in the real world. You will develop and integrate AI/ML pipelines with ROS/ROS2 systems, and leverage NVIDIA robotics frameworks (e.g., Isaac ROS, Isaac Sim, Omniverse, Jetson, TensorRT) to deliver production-grade capabilities such as perception, sensor fusion, navigation, manipulation, and autonomy.

You will work closely with robotics engineers, platform teams, and product stakeholders to move solutions from simulation → real robot deployment, ensuring performance, reliability, and safety.

Key Responsibilities

1) Physical AI / Robotics AI Development

Build AI/ML solutions for robotics use cases: perception (2D/3D), localization, mapping, planning, control, manipulation, and autonomy.

Develop and fine-tune models for computer vision, 3D point cloud processing, multi-sensor fusion (camera, LiDAR, radar, IMU), and behavior prediction.

Apply real-time constraints and optimize for edge deployment.

2) ROS/ROS2 System Integration

Develop ROS/ROS2 nodes, packages, and pipelines integrating sensors, ML inference, and robotics stacks.

Integrate AI components with ROS ecosystem: Nav2, TF2, rosbag, URDF, RViz, Gazebo/Isaac Sim interfaces, message filters, and lifecycle management.

Ensure robust performance under latency, bandwidth, and compute constraints (real robots).

3) NVIDIA Robotics Frameworks (Isaac / Omniverse / Jetson)

Build accelerated perception and autonomy pipelines using NVIDIA Isaac ROS, GXF/NITROS, and GPU-accelerated components.

Use Isaac Sim / Omniverse to generate synthetic data, validate behaviors, and perform sim-to-real testing.

Deploy on NVIDIA hardware (e.g., Jetson, GPU servers) with TensorRT, CUDA, and optimized runtime configurations.

4) Model Deployment, Optimization & Edge Inference

Convert and optimize models using ONNX, TensorRT, quantization (FP16/INT8), and performance profiling.

Implement real-time inference pipelines, optimize CPU/GPU utilization, and validate throughput/latency targets.

Establish reliability practices: health checks, fail-safe modes, and runtime monitoring.

5) Data, Training, Evaluation & Experimentation

Design training data strategy: collection, labeling, augmentation, and synthetic data generation.

Define metrics and evaluation frameworks: accuracy + robotics KPIs (latency, drift, stability, success rate, collision rate).

Manage experiment tracking and reproducibility (e.g., MLflow/W&B equivalent) and model versioning.

6) Engineering Excellence & Collaboration

Lead technical design discussions, mentor engineers, and contribute to architecture decisions.

Work cross-functionally with hardware, firmware, robotics, cloud, and product teams.

Produce clear documentation and guide best practices for production robotics AI.

Required Qualifications

Bachelor’s/Master’s in Computer Science, Robotics, Electrical/Mechanical Engineering, or related field.

5+ years experience in AI/ML engineering, including robotics/embedded/edge AI exposure.

Strong hands-on programming in Python and C++ (robotics-grade engineering).

Strong ROS/ROS2 experience: building, debugging, and deploying ROS pipelines.

Practical experience with deep learning frameworks: PyTorch (preferred) or TensorFlow.

Experience with perception or robotics domains: CV, sensor fusion, SLAM concepts, motion planning, or manipulation.

Linux development, Docker, CI/CD fundamentals, and software testing practices.

Preferred / Nice-to-Have Skills

NVIDIA robotics stack experience: Isaac ROS, Isaac Sim, Omniverse, Jetson deployment, CUDA, TensorRT.

3D vision / geometry: point clouds, depth, stereo, Open3D/PCL, ICP concepts.

Navigation/Autonomy: Nav2, costmaps, planners, controllers, SLAM toolchains (e.g., RTAB-Map, Cartographer).

Robotics simulators: Gazebo, Isaac Sim, Mujoco; sim-to-real workflows.

Knowledge of safety & reliability: watchdogs, redundancy, safe states, operational envelopes.

Experience with real robot platforms: mobile robots, AMRs, drones, robotic arms.

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

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Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

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