[EAF] Lead AI Engineer

The Bosch Group is a leading global supplier of technology and services. Its operations are divided into four business sectors: Mobility, Industrial Technology, Consumer Goods, and Energy and Building Technology. With technology that is “Invented for life,” Bosch wants to help improve quality of life and conserve natural resources.

The Bosch Group comprises Robert Bosch GmbH and its roughly 490 subsidiary and regional companies in over 60 countries. Including sales and service partners, Bosch’s global manufacturing, engineering, and sales network covers nearly every country in the world. Bosch’s innovative strength is key to the company’s further development.

Bosch Global Software Technologies Company Limited (BGSV)is 100% owned subsidiary of Robert Bosch GmbH, offering end-to-end Engineering, IT, and Business Solutions.

Starting its operation from 2010 at Etown 2 in HCMC, BGSV is the first software development center of Bosch in Southeast Asia. BGSV nowadays have over 4,000 associates, with a global footprint and presence in the US, Europe, and the Asia Pacific region. With our unique ability to offer end-to-end solutions that connect sensors, software, and services, we enable businesses to move from the traditional to digital or improve businesses by introducing a digital element in their products and processes.

BGSV currently operates from three offices located at the following addresses:

1. Etown Building – 364 Cong Hoa Street, Ward 13, Tan Binh District, Ho Chi Minh City, Vietnam

2. OfficeHaus Building – 32 Tan Thang Street, Son Ky Ward, Tan Phu District, Ho Chi Minh City, Vietnam

3.Capital Place Building – 29 Lieu Giai Street, Ngoc Khanh Ward, Ba Dinh District, Hanoi, Vietnam

The Lead Engineer - AI is responsible for designing and developing artificial intelligence and machine learning models to address business and technical requirements. This role owns key technical topics within the AI domain, guiding team members in the implementation of robust and scalable solutions across product portfolios.

Main Roles and Responsibilities

1. Design and develop AI/ML solutions, including computer vision, GenAI, natural language processing, and predictive analytics, to meet project specifications as per communication and alignment with customer or customer interface.
2. Lead the implementation of the full lifecycle of AI/ML solutions, from data acquisition and preprocessing to model deployment and monitoring.
3. Own the technical design and architecture for specific AI/ML solutions and features within larger engineering applications.
4. Conduct in-depth data analysis and feature engineering to extract insights and improve model accuracy and robustness.
5. Implement MLOps best practices, including version control for data and models, automated testing, and CI/CD pipelines for machine learning systems and drive innovation.
6. Mentor junior engineers on AI/ML concepts, coding best practices, and the use of modern data science tools and frameworks.
7. Apply advanced machine learning frameworks including TensorFlow, PyTorch and statistical methods to build, train, and validate high-performance models.
8. Guide team members in resolving complex technical challenges and ensure the quality and integrity of AI/ML work products through technical reviews.
9. Ensure compliance with applicable industry standards, regulatory requirements, company policies, and quality frameworks applicable to the role and assigned projects.
10. Perform other tasks as assigned by Managers.

Job Requirements

Experience

• Proven professional experience in developing and deploying machine learning models and AI systems.
• Proven experience with modern ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and MLOps practices.
• Experience in owning technical topics and mentoring junior team members is required.

Professional Competence

• AI Agents/Frameworks.
• Data Annotation Basics.
• Data Modelling and Design.
• Generative AI.
• Image Processing Libraries (OpenCV).
• LangChain/LlamaIndex.
• Large Language Models (LLMs).
• Machine Learning.
• MLOps / ML Lifecycle Management.
• Model Based Development.
• Model Validation & Evaluation.
• Natural Language Processing (NLP).
• Neural Network Architectures.
• Python (Programming Language).
• PyTorch.
• Vector DB.
• Code Review
• Solution Design
• Problem Solving.
• Proficient in English Communication
• Proficien…