Appletree Global Consulting
Robotics Algorithm Engineer (Perception, Scene Reconstruction & Human-Centric AI)
We are seeking a highly skilled Robotics Algorithm Engineer to join our core R&D team and help build next‑generation embodied AI systems. In this role, you will develop cutting‑edge algorithms across visual perception, 3D scene understanding, robot learning, and multi‑sensor fusion and deploy them directly on real robotic platforms impacting production‑level systems.
What Youll Do
Develop and deploy algorithms for perception, 3D reconstruction, visual SLAM/VIO, and autonomous scene understanding.
Build robot learning pipelines including imitation learning, reinforcement learning, and foundation model fine‑tuning.
Create data‑driven models leveraging large‑scale egocentric and human‑robot datasets.
Architect robust multi‑sensor fusion frameworks integrating vision, proprioception, and tactile sensing.
Implement production‑level software using
ROS/ROS2 , C++, and Python.
Test, benchmark, and optimize algorithms on physical robotic systems.
Collaborate cross‑functionally on data generation, model evaluation, and system‑level optimization.
Contribute to publications, patents, and internal technical roadmaps.
Mentor junior engineers and support a culture of innovation.
Minimum Qualifications
MS or PhD in Robotics, CS, EE, or related field (or equivalent experience).
3+ years experience in robotics, computer vision, or ML for embodied systems.
Strong C++ & Python skills; experience with
ROS/ROS2 .
Solid grounding in 3D geometry, optimization, and estimation.
Experience in one or more:
Visual SLAM / VIO / multi‑view geometry
3D reconstruction / mapping
Sensor fusion & state estimation
Robot learning (IL, RL, or foundation model adaptation)
Previous deployment of algorithms on
real robotic hardware .
Preferred Qualifications
PhD with research in robot learning, embodied AI, or visual perception.
Deep knowledge of PyTorch/TensorFlow.
Experience with imitation learning, reinforcement learning, and policy optimization.
Experience with CLIP, RT‑1, VLA, or similar VLM/robotics foundation models.
Background in 3D human modeling, MoCap, or human‑to‑robot demonstrations.
CUDA, multi‑threading, or distributed training experience.
Publications in ICRA, IROS, CoRL, RSS, CVPR, ICCV, NeurIPS.
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We are seeking a highly skilled Robotics Algorithm Engineer to join our core R&D team and help build next‑generation embodied AI systems. In this role, you will develop cutting‑edge algorithms across visual perception, 3D scene understanding, robot learning, and multi‑sensor fusion and deploy them directly on real robotic platforms impacting production‑level systems.
What Youll Do
Develop and deploy algorithms for perception, 3D reconstruction, visual SLAM/VIO, and autonomous scene understanding.
Build robot learning pipelines including imitation learning, reinforcement learning, and foundation model fine‑tuning.
Create data‑driven models leveraging large‑scale egocentric and human‑robot datasets.
Architect robust multi‑sensor fusion frameworks integrating vision, proprioception, and tactile sensing.
Implement production‑level software using
ROS/ROS2 , C++, and Python.
Test, benchmark, and optimize algorithms on physical robotic systems.
Collaborate cross‑functionally on data generation, model evaluation, and system‑level optimization.
Contribute to publications, patents, and internal technical roadmaps.
Mentor junior engineers and support a culture of innovation.
Minimum Qualifications
MS or PhD in Robotics, CS, EE, or related field (or equivalent experience).
3+ years experience in robotics, computer vision, or ML for embodied systems.
Strong C++ & Python skills; experience with
ROS/ROS2 .
Solid grounding in 3D geometry, optimization, and estimation.
Experience in one or more:
Visual SLAM / VIO / multi‑view geometry
3D reconstruction / mapping
Sensor fusion & state estimation
Robot learning (IL, RL, or foundation model adaptation)
Previous deployment of algorithms on
real robotic hardware .
Preferred Qualifications
PhD with research in robot learning, embodied AI, or visual perception.
Deep knowledge of PyTorch/TensorFlow.
Experience with imitation learning, reinforcement learning, and policy optimization.
Experience with CLIP, RT‑1, VLA, or similar VLM/robotics foundation models.
Background in 3D human modeling, MoCap, or human‑to‑robot demonstrations.
CUDA, multi‑threading, or distributed training experience.
Publications in ICRA, IROS, CoRL, RSS, CVPR, ICCV, NeurIPS.
#J-18808-Ljbffr