Data Scientist

At STMicroelectronics, we believe in the power of technology to drive innovation and make a positive impact on people, businesses, and society. As a global semiconductor company, our advanced technologies and chips form the hidden foundation of the world we live in today.
When you join ST, you will be part of a global business with more than 115 nationalities, present in 40 countries, and comprising over 50,000 diverse and dedicated creators and makers of technology around the world.
Developing technologies takes more than talent : it takes amazing people who understand collaboration and respect. People with passion and the desire to disrupt the status quo, drive innovation, and unlock their own potential.
Our technology starts with you.
STMicroelectronics Malta is seeking a skilled and motivated AI Data Scientist who leads the design, deployment, and continuous improvement of physical assets to augment or replace manual tasks in semiconductor manufacturing environments.
Develop, train, and validate embodied AI models leveraging Vision-Language Models (VLM) and Vision-Language-Action (VLA) frameworks to enable integrated perception, natural language understanding, and task execution capabilities.
Utilize NVIDIA Omniverse or similar simulation platforms for high-fidelity 3D simulation and digital twin environments to train, test, and optimize physical assets AI models in realistic virtual manufacturing settings.
Integrate multimodal data (image, sensor, process logs, SPC data) into AI models for robust decision-making and adaptive control.
Collaborate with robotics vendors to adapt physical assets or semiconductor environments (cleanroom compliance, ESD safety, precision control).
Integrate AI models with physical asset control systems and factory MES / SCADA systems.
Simulation and Virtual Training Environment Development
Design and maintain simulation scenarios within Omniverse / similar platform to replicate manufacturing processes and environments for embodied AI training.
Employ VLM and VLA techniques to simulate realistic robot-environment interactions, enabling the AI to learn visual perception coupled with language understanding and action planning.
Validate AI behavior in virtual environments before physical deployment to reduce risk and improve efficiency.
Testing, Validation, and Qualification
Define test plans to validate robot / physical asset accuracy, repeatability, and safety before deployment.
Establish qualification metrics : task success rate, downtime reduction, human replacement efficiency.
Deployment and Continuous Improvement
Lead pilot projects for physical manufacturing asset-assisted lines and scale up successful deployments.
Analyze performance data, identify model drift or mechanical degradation, and retrain models as needed.
Conduct root-cause analysis for failed or abnormal tasks.
Work closely with process engineers, maintenance teams, IT, and data scientists.
Train human technicians to supervise and interact with physical manufacturing assets systems safely.
Bachelor's or Master's degree in Robotics, AI / ML, Mechatronics, Electrical Engineering, or Computer Science.
Strong understanding of semiconductor manufacturing processes (Front-End and / or Back-End).
Proficiency in AI / ML model development (Python, TensorFlow / PyTorch, OpenCV).
Experience with embodied AI frameworks such as Vision-Language Models (VLM) Vision-Language-Action (VLA) for integrated perception, language understanding, and action modeling.
Hands-on experience with NVIDIA Omniverse or similar simulation platforms for digital twin and virtual training environments.
Knowledge of robot control systems (ROS, PLC interfacing, motion planning).
Familiar with machine vision systems, defect detection, and sensor fusion.
Experience in cloud technologies is added advantage.
Clear communication between data science, robotics, and operations teams.
3–5 years' experience in semiconductor manufacturing, robotics automation, or AI model deployment. Experience deploying AI / vision models in industrial environments (manufacturing, automotive, electronics) is a plus.
Prior experience with embodied AI training using VLM, VLA, and Omniverse highly desirable.
This role may require candidate to travel between different manufacturing sites of the company.
Experience with cleanroom operation or ISO 14644 standards preferred.
ST is proud to be one of the 17 companies certified as a 2025 Global Top Employer and the first and only semiconductor company to achieve this distinction. ST was recognized in this ranking thanks to its continuous improvement approach and stands out particularly in the areas of ethics & integrity, purpose & values, organization & change, business strategy, and performance.
We strive for equity in career development, career opportunities, and equal remuneration. Diversity, equity, and inclusion (DEI) is woven into our company culture.