Role: You are the strategic mind behind our AI systems. You design the overall architecture of our autonomous solutions, ensuring that all components work together seamlessly and achieve our long-term automation goals.

Required Skills & Experience:

• Proven Experience: At least 10 years of experience in designing and implementing complex, scalable AI systems in production environments.

• Architecture Expertise: Deep understanding of microservices, cloud architectures (AWS, Azure, GCP), data pipelines, and MLOps.

• Broad AI Knowledge: Profound knowledge in various AI fields (ML, DL, NLP, CV, RL) and the ability to select the best approaches for specific problems.

• Strategic Thinking: Ability to define technical roadmaps and make decisions that impact long-term scalability and maintainability.

• Leadership: Experience in technical leadership of teams and mentoring junior engineers.

Challenges:

• Designing and implementing end-to-end architectures for fully autonomous operations.

• Ensuring the scalability, reliability, and security of our AI infrastructure.

• Evaluating and integrating new AI technologies and frameworks.

• Bridging the gap between various technical teams (ML Engineering, Robotics, Software Development).

Role: You are the expert in developing, implementing, and optimizing machine learning models. Your task is to bring cutting-edge AI algorithms from research to production readiness, driving our automation solutions.

Required Skills & Experience:

• ML Expertise: At least 5 years of experience in developing and deploying ML models (Scikit-learn, TensorFlow, PyTorch).

• Programming: Excellent Python skills; experience with other languages like C++ or Java is a plus.

• Data Processing: Experience with large datasets and data pipelines (SQL, NoSQL, Spark, Kafka).

• Model Optimization: Knowledge of hyperparameter tuning, model validation, and deployment strategies.

• MLOps Fundamentals: Understanding of Continuous Integration/Deployment (CI/CD) in the context of ML.

Challenges:

• Developing and optimizing customized ML models for specific automation tasks (e.g., predictive maintenance, supply chain optimization).

• Deploying models in production environments and monitoring their performance.

• Working with unstructured data and complex datasets.

• Ensuring the robustness and interpretability of the developed models.

Role: You are the specialist for the interface between software and hardware. Your expertise enables our robots to intelligently interact with their environment, perform tasks autonomously, and adapt to new circumstances.

Required Skills & Experience:

• Robotics Frameworks: Extensive experience with ROS (Robot Operating System) and/or other common robotics frameworks.

• Programming: Excellent C++ and Python skills.

• Sensors & Actuators: Experience with the integration and processing of sensor data (LIDAR, cameras, IMUs) and the control of actuators.

• Motion Planning: Knowledge of kinematics, trajectory planning, and collision avoidance.

• Computer Vision (optional but highly desirable): Experience with image processing for robotic applications.

Challenges:

• Developing software for autonomous mobile robots and manipulators.

• Integrating AI models for perception, navigation, and manipulation.

• Optimizing real-time performance and ensuring the safety of robotic systems.

• Troubleshooting and debugging complex hardware and software interactions.

Role: You are our thought leader, tracking the latest research findings in the field of AI and translating them into innovative solutions for our companies. You experiment with new algorithms and techniques to give us a competitive edge.

Required Skills & Experience:

• Academic Background: PhD in AI, Computer Science, Mathematics, or a related field.

• Research Experience: Proven publications in reputable AI conferences (NeurIPS, ICML, ICLR, AAAI, CVPR, ACL).

• Broad Knowledge: Deep understanding of advanced AI concepts such as Reinforcement Learning, Generative Models, Causality, or Multi-Agent Systems.

• Programming: Solid programming skills in Python and common ML frameworks.

• Prototyping: Ability to quickly develop and validate research prototypes.

Challenges:

• Identifying promising research areas and their applicability to our business models.

• Developing and evaluating novel AI algorithms and models.

• Collaborating with ML engineers to transition research findings into production systems.

• Building a research culture that fosters innovation and experimentation.

Role: You are the bridge between data, models, and production. As a Data Scientist, you analyze data to gain insights that drive our AI development. As an MLOps Engineer, you ensure that our AI models are efficiently developed, tested, deployed, and monitored.

Required Skills & Experience:

• Data Analysis: Strong skills in statistical analysis, data visualization, and data cleaning.

• SQL & Big Data: Experience with relational and non-relational databases as well as Big Data technologies (e.g., Spark, Hadoop).

• MLOps Tools: Experience with tools like Kubeflow, MLflow, Airflow, Docker, Kubernetes.

• Scripting: Solid Python and Bash scripting skills.

• Cloud Knowledge: Experience with cloud platforms and their ML services.

Challenges:

• Building and maintaining robust data pipelines for training and inference data.

• Automating the entire lifecycle of ML models (training, validation, deployment, monitoring).

• Ensuring data quality and model integrity.

• Implementing monitoring systems to detect model drift and performance deviations.