About the role

As an AI Algorithm Developer, you will help develop, validate, and productize intelligent algorithms for our Physical AI stack in China. You will work with the existing Suzhou Physical AI team on Level 2 robotics skills, including picking and placing, packing, palletizing, motion planning, perception, and adaptive robot behavior.

This role combines machine learning research and engineering with reinforcement learning and robotics application development. You will turn algorithmic ideas into measurable, maintainable capabilities that can be integrated, tested, deployed, and improved in real industrial environments.

If you enjoy solving complex perception, decision-making, and control problems with Python, machine learning, and reinforcement learning, this role offers the opportunity to shape practical Physical AI solutions.

Key responsibilities

• Designing, implementing, training, and evaluating machine learning and reinforcement learning algorithms for robotics and Physical AI use cases

• Developing perception, decision-making, planning, policy-learning, and adaptive behavior capabilities for industrial robotics applications

• Building reproducible data, training, simulation, evaluation, and experiment-management pipelines

• Defining baselines, metrics, benchmarks, ablation studies, and acceptance criteria to measure algorithm performance and robustness

• Working with simulation and real robotic systems to address sim-to-real transfer, domain variation, safety constraints, and operational reliability

• Optimizing models and inference pipelines for latency, compute, memory, and deployment constraints in edge or industrial environments

• Packaging algorithms as maintainable software components or services with clear interfaces, documentation, tests, and versioning

• Analyzing failures, data quality, model behavior, and edge cases, then translating findings into systematic improvements

• Collaborating with robotics engineers, full stack developers, architects, DevOps engineers, and domain experts

• Supporting integration, validation, and troubleshooting in lab, pilot, and customer-oriented environments

• Following responsible AI, secure development, data governance, and software quality practices

Required qualifications

• Degree in Computer Science, Artificial Intelligence, Robotics, Automation, Applied Mathematics, or a related field, or equivalent practical experience

• Studying abroad is a plus, but not required

• 5+ years of experience in AI algorithm development, machine learning engineering, reinforcement learning, robotics research, or a related field

• Strong hands-on programming experience with Python

• Strong foundation in machine learning, including model training, evaluation, generalization, and data-driven experimentation

• Hands-on experience with reinforcement learning, including environment design, policy training, reward design, evaluation, and debugging

• Experience with at least one mainstream machine learning framework and scientific computing toolchain

• Solid understanding of probability, statistics, optimization, linear algebra, and algorithmic problem solving

• Ability to write maintainable research and production code with source control, testing, documentation, and reproducible experiments

• Practical problem-solving mindset and ability to move from research concepts to validated engineering solutions

Preferred qualifications

• Experience applying reinforcement learning to robotics, manipulation, motion planning, control, or sequential decision-making

• Experience with computer vision, multimodal learning, foundation models, vision-language models, or vision-language-action models

• Familiarity with robot simulation, synthetic data, imitation learning, offline reinforcement learning, or sim-to-real methods

• Experience deploying and optimizing models on GPU-enabled edge or industrial computing platforms

• Familiarity with MLOps, experiment tracking, dataset versioning, model monitoring, containers, and CI/CD

• Knowledge of industrial automation, robot safety constraints, hardware/software integration, or real-time systems

• Experience working at a multinational corporation (MNC) is a plus

Languages

• Fluency in English and Chinese

Ways of working

• You are hypothesis-driven, analytical, and highly execution-oriented

• You make algorithmic decisions based on measurable evidence and reproducible experiments

• You can work independently while aligning with broader product, architecture, and safety needs

• You communicate complex algorithmic topics clearly to cross-functional stakeholders

• You are curious about new research and disciplined about turning it into robust engineering

What we offer you

• Attractive remuneration package aligned with local market conditions

• Flexible working models where applicable

• Continuous learning and technical growth in industrial AI, robotics software, and modern engineering practices

• Opportunity to shape products and engineering capabilities for a strategically important robotics team

• Collaboration with local and global experts across robotics, software, and industrial AI

• Innovative environment focused on real industrial use cases and customer impact

The individual benefits are subject to local regulatory, contractual, or corporate conditions.

About us

At Siemens Digital Industries Factory Automation, we are building the software and automation capabilities that enable the next generation of intelligent manufacturing. In Smart Robotics, robust AI algorithms are essential for enabling robots to perceive, decide, learn, and act effectively in variable industrial environments.

If you want to turn advanced machine learning and reinforcement learning into reliable robotics capabilities with real customer impact, we look forward to meeting you.