Envision the future with Sentigent

Machine Learning Engineer (ML Engineer)

Suzhou Full-time Competitive Salary

Job Responsibilities

  1. Responsible for research in cutting-edge technologies such as deep learning, image understanding, and machine learning, maintaining industry leadership and continuously breaking through technical limits.
  2. Responsible for the development and performance improvement of computer vision and deep learning algorithms, involving but not limited to: object detection, segmentation, recognition, tracking and other CV algorithms; face and human body keypoint detection; scene understanding based on multi-modal VLM models; end-to-end autonomous navigation models for robots.
  3. Algorithm engineering, including model engineering and optimization work.

Job Requirements

  1. Master's degree or above, with background in computer science, information engineering, electronic engineering, automation, mathematics, statistics, or related fields.
  2. Excellent problem analysis and solving abilities, curiosity for new technologies, willingness to tackle difficult challenges, and ability to propose solutions and quickly validate them.
  3. Familiar with one of the open-source deep learning frameworks for computer vision such as Pytorch/TensorFlow.
  4. Strong coding ability. Familiar with Linux, C/C++ and Python, excellent coding and code control skills, solid foundation in data structures and algorithms.
  5. Familiar with CUDA programming, CUDNN, or TensorRT preferred, experience in image algorithm performance optimization preferred.
  6. Strong research capabilities, with preference for those who have published papers at conferences such as CVPR/ICCV/ECCV/NIPS/ICML/SIGGRAPH.

Robot Motion Control Engineer

Suzhou Full-time Competitive Salary

Job Responsibilities

  1. Responsible for the research and development of motion control and planning control algorithms for legged/wheeled robots, covering simulation environments and actual robot platforms.
  2. Design and implement gait generation algorithms and motion planning strategies suitable for different tasks.
  3. Develop obstacle avoidance and autonomous navigation algorithms for robots in dynamic environments, improving motion robustness and environmental adaptability.
  4. Collaborate with hardware/perception/deployment teams to promote the integration and optimization of control systems on various robot platforms.
  5. Continuously follow and track cutting-edge algorithms, promoting iteration and performance improvement of control strategies.

Job Requirements

  1. Master's degree or above in control, automation, computer science, robotics, or related fields.
  2. Priority given to candidates with research background in:
    1. Automatic control principles, modern control theory
    2. Optimal control, model predictive control (MPC)
    3. Robot kinematics and dynamics modeling
  3. Priority given to those with experience in legged robot or wheeled robot motion control algorithm development, including but not limited to:
    1. Gait planning / gain tuning / motion sequence generation
    2. State estimation / inertial fusion / foot force control
  4. Familiar with mainstream control and simulation toolchains, such as:
    1. PyBullet, Isaac Gym, Gazebo, Mujoco and other simulation platforms
    2. Rigid body dynamics libraries (such as Pinocchio, RBDL, Drake, etc.)
  5. Proficient in C++/Python, with good engineering implementation capabilities and code structure design skills.
  6. Priority given to those with experience in reinforcement learning/imitation learning algorithms, able to integrate learning strategies in control tasks.
  7. Solid mathematical foundation, especially in linear algebra, optimization, control system modeling and analysis.
  8. Fast learner of new things, strong oral and written communication skills, able to effectively collaborate with cross-functional teams.

High Performance Computing Engineer (HPC Engineer)

Suzhou Full-time Competitive Salary

Job Responsibilities

  1. Responsible for the deployment of robot perception, LLM, speech and other models, accelerating solution implementation, function development and debugging.
  2. Responsible for developing and maintaining software frameworks for AI modules.
  3. Responsible for deploying perception deep learning models on Nvidia GPU platforms and developing function integration.
  4. Responsible for joint debugging, testing follow-up and iterative optimization after function development completion.
  5. Responsible for hardware resource usage evaluation and performance optimization.

Job Requirements

  1. Bachelor's degree or above in electronics/communications/computer science/automation or related fields, with 3+ years of AI model engineering deployment development experience.
  2. Solid foundation in C++, CUDA, Python programming, sufficient mastery of multi-threading, data structures, and algorithm basics, deep understanding of algorithm optimization and acceleration, with CUDA acceleration experience.
  3. Proficient in asynchronous acceleration solutions such as coroutines under Linux, able to develop and debug proficiently on Linux systems, able to efficiently write data analysis and automated processing scripts.
  4. Proficient in GPU profiling tools such as NSight.
  5. Familiar with common algorithm structures such as transformer, CNN, RNN for vision and speech.
  6. Good code writing standards and documentation writing skills.
  7. Excellent problem analysis, communication and collaboration skills, strong sense of responsibility, love for research. Entrepreneurial mindset.
  8. Practical experience in deep learning model deployment, TensorRT plugin implementation, GPU performance optimization preferred.

Bonus Points

  1. Experience with model pruning, quantization, etc.
  2. Experience with model training
  3. Background in robotics or autonomous driving industry
  4. Good English communication and reading skills
  5. Experience with deployment and optimization on chips other than Nvidia, such as Horizon Robotics, Black Sesame Technologies, etc.
  6. Linux troubleshooting ability (solving coredump, CUDA acceleration profiling)

Reinforcement Learning Engineer (Robotics)

Suzhou or Shenzhen Full-time Competitive Salary

Job Responsibilities

  1. Develop deep reinforcement learning algorithms for multi-degree-of-freedom robots (such as bipedal, quadrupedal, wheeled-legged robots, etc.);
  2. Design and implement strategies for agents to perform stable motion, balance control, and obstacle avoidance tasks in complex environments;
  3. Build and maintain robot reinforcement learning simulation training platforms, promoting effective transfer of algorithms from simulation to real physical robots (Sim2Real);
  4. Responsible for reproduction, model development, debugging and real machine deployment of deep reinforcement learning algorithms;
  5. Develop automated deployment tools to support rapid iteration of algorithms on actual robot platforms;
  6. Write and maintain related technical documentation, participate in internal technical exchanges and collaboration within the team.

Job Requirements

  1. Master's degree or above, exceptionally outstanding candidates can be relaxed to bachelor's degree, with solid foundation in robot kinematics and dynamics;
  2. Familiar with ROS/ROS2 system structure and working mechanism, proficient in one or more programming languages in C++ and Python;
  3. Familiar with robot simulation software such as Mujoco, Gazebo, NVIDIA Isaac, Bullet, etc.;
  4. Master common deep reinforcement learning algorithms (such as DQN, DDPG, A3C, PPO, etc.) theory and application;
  5. Familiar with at least one deep learning framework (such as PyTorch, TensorFlow), with practical project development experience;
  6. Understand Sim2Real key technologies, such as motor modeling, communication delay, sensor noise modeling and perception simulation;
  7. Strong interest in robotics technology and AI reinforcement learning, willing to explore, strong communication and hands-on skills.

Bonus Points

  1. Experience in robot-oriented deep reinforcement learning projects or productization
  2. Published papers in top conferences/journals in AI/robotics field (such as NeurIPS, ICRA, IROS, CVPR, AAAI, CoRL, T-PAMI, etc.)
  3. Familiar with basic computer vision or 3D perception
  4. Experience in strategy training, debugging and deployment on actual robot platforms

Robot Motion Planning and Control Algorithm Engineer

Suzhou Full-time Competitive Salary

Job Responsibilities

  1. Develop robot path planning algorithms, optimize the efficiency and robustness of path planning algorithms
  2. Handle path generation and adjustment problems in dynamic environments, solve obstacle avoidance problems in complex scenarios
  3. Research and implement robot action decision algorithms, design task decomposition and behavior selection logic

Job Requirements

  1. Master's degree or above in robotics, computer science, electronics, communications, automation and related fields
  2. Solid foundation in Modern C++, Linux, network communication, etc., familiar with Python, Shell and other scripting languages;
  3. Familiar with path planning algorithms (A*, RRT, DWA, etc.) and behavior decision frameworks, with practical development experience;
  4. Familiar with simulation tools (such as Gazebo, Webots, Mujoco, etc.), able to build test environments and debug;
  5. Good learning ability and technical research spirit;
  6. Team collaboration skills, able to cooperate with hardware, embedded and other algorithm teams to complete complex tasks.

Bonus Points

  1. Experience in robot navigation, autonomous driving or drone control related projects
  2. Published high-level papers in robotics, reinforcement learning, imitation learning and other fields or open source project experience

C++ System Architecture and Algorithm Engineer (Control Focus)

Suzhou Full-time Competitive Salary

Job Responsibilities

  1. Participate in the design, integration and optimization of control algorithm modules in robot systems, focusing on building and maintaining high-performance C++ software architecture
  2. Use modern C++ to write efficient, modular, and scalable control algorithm frameworks (supporting RL, trajectory planning, MPC, feedforward control, etc.)
  3. Collaborate with reinforcement learning algorithm engineers and embedded system engineers to implement deployment and debugging of control algorithms on edge computing devices (ARM/NPU/FPGA);
  4. Participate in system integration of state estimation and closed-loop control modules based on sensor data (such as encoders, IMU);
  5. Responsible for simulation, unit testing, integration testing and performance tuning of control modules, output related technical documentation;
  6. Introduce advanced software architecture and algorithm design concepts while ensuring system stability and computational efficiency, promoting system evolution.

Job Requirements

  1. Education requirements: Bachelor's degree or above in computer science, software engineering, automation, control engineering, robotics and related majors;
  2. Programming skills: Proficient in C/C++, master modern C++ (C++11 and above) programming paradigms, excellent software architecture design capabilities, familiar with multi-threaded programming, memory management and modular development;
  3. System experience: Experience in C++ architecture design for large software projects or robot system related modules;
  4. Familiar with cross-platform development, compilation and debugging toolchains, familiar with embedded deployment processes preferred;
  5. Collaboration and debugging: Cross-team collaboration experience, able to work closely with algorithm, embedded, system engineering and other parties to complete project closure.

Bonus Points

  1. Familiar with basic principles of control algorithms (such as PID, MPC, etc.)
  2. Experience with simulation platforms such as ROS2, Mujoco, Isaac Gym, Gazebo
  3. Experience in robot kinematics/dynamics modeling, motor control or autonomous driving
  4. Experience in robot control system launch or edge deployment

What We Hope You Have

  1. Clear code style and solid engineering literacy
  2. Strong system awareness and performance sensitivity
  3. Good logical thinking, communication skills and team collaboration spirit