Subsystem AI Engineer
Lenovo (Schweiz) GmbH
Publication date:
15 September 2024Workload:
100%Contract type:
Unlimited employment- Place of work:Chur
Why Work at Lenovo
Description and Requirements
As a Subsystem AI Engineer, you will harness data generated by PC subsystems, particularly focusing on battery and wireless technologies, to enhance user experiences with our PC devices. You will work closely with suppliers and system development teams to identify and access critical data, and develop advanced machine learning (ML) and artificial intelligence (AI) algorithms to optimize the use of this data. Additionally, collaboration with other business units such as Services and Quality Assurance will be integral to your role.
Key Responsibilities:
- Battery Data Analysis: Utilize battery data to model and analyze user behavior and power consumption, identifying trends and differences across various brands, geographies, and product portfolios.
- Wi-Fi Connectivity Improvement: Develop methods to enhance Wi-Fi connectivity by leveraging on-board telemetry and data analytics.
- Qualification vs. Field Data Evaluation: Assess and compare qualification data with field data to refine and validate test processes for accuracy and efficiency.
- AI Battery Charge Control: Lead the development and implementation of AI-driven battery charge control proof-of-concept (PoC) projects, ensuring seamless integration with the broader system architecture.
- Collaboration: Partner with suppliers, system development teams, and other business groups (e.g., Services, Quality Assurance) to drive projects and ensure alignment with overall business objectives.
Basic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related field.
- 5+ yearss proven experience in machine learning, artificial intelligence, or data analysis, particularly related to PC subsystems such as battery and wireless technologies.
- Proficiency in programming languages such as Python, C++, or Java. Experience with ML/AI frameworks and tools (e.g., TensorFlow, PyTorch) is essential.
- Strong analytical and problem-solving abilities with a focus on data-driven insights and decision-making.
- Excellent communication and collaboration skills, with the ability to work effectively across different teams and business units.