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- In-Vehicle AI Technology Development AI Engineer
JOB ID 27340
In-Vehicle AI Technology Development AI Engineer
- Manufacturer, Electrical & Electronic
- IT, SE(Control, Embedded), Data Analyst, SE(Web, OPEN), Product Engineer (Hard/soft)
- Tokyo, Aichi
- ¥9,000,000～¥14,300,000
We are a company boasting one of the top domestic market shares in the automotive parts industry, specializing in thermal systems, mobility systems, power train systems, electrification systems, and electronic systems.
Currently, we are focusing on four areas: electrification, connectivity, advanced safety/autonomous driving, and non-vehicle businesses (FA/agriculture). In particular, in the field of autonomous driving, we are conducting demonstration experiments on public roads for Level 4 autonomous driving, working toward the future of safe and secure mobility systems.
Products equipped with machine learning/AI are rapidly penetrating society, and AI is beginning to be used in areas such as autonomous driving and cockpits, as well as in safety, security, and comfort. At the same time, expectations are rising, and there is an increasing demand for continuous rapid evolution.
For cars to continue evolving rapidly after entering the market, various insights are required, including integration between cars and the cloud, generative AI, vision-based AI, and agent AI.
We are now looking for colleagues who can work together in this new field.
* For this position, to enhance matching between both parties,
we will conduct a job briefing interview in parallel with the document screening.
(Content: alignment of organization, business content, and skills)
Job Description
-
- Responsibilities
– Creating in-vehicle AI that enables cars to think, learn, and evolve on their own
You will lead the overall design of vision models such as ViT/VLM, which are central to automotive AI, multimodal AI, LLM/SLM, and the development of cloud integration platforms.
✦ Specific Tasks
Architectural Design for In-Vehicle AI
Design of the entire in-vehicle AI including vision models such as ViT/VLM, multimodal AI, and LLM agents. Specification development with an eye on inference, decision-making, control, and UX integration
AI Model Development, Training, and Optimization (MLOps Platform Construction)
Design for data collection, preprocessing, learning, and evaluation. Model advancement based on edge implementation, including distillation, quantization, and inference optimization. Experiment management, model versioning, and building an automated evaluation environment.
Construction of in-vehicle data collection and utilization infrastructure. Collection and analysis of image, audio, and vehicle data. Building data analysis platforms and ActiveLearning platforms utilizing market data.
Design and operation of cloud-integrated AI platforms, design of learning pipelines on the cloud, and construction of DevOps environments including CI/CD and OTA integration
Promoting the cycle of actual vehicle evaluation and improvement. Specification adjustments across software, hardware, and cloud. Performance evaluation and improvement through actual vehicle inspections.
Exploring the latest AI technologies and creating intellectual property. Latest algorithm trend survey. Consideration of automotive application and patent creation. Exploring AI-related technologies in society and considering their application in automotive applications
-
- Requirements
Data analysis and machine learning: Over 1 year of development experience with Python; libraries used: NumPy, Pandas, Plotly, scikit-learn, statsmodels, Optuna, etc., capable of data analysis and output using statistical methods.
Experience in model development (over 1 year), able to handle the entire process from design, learning, evaluation, to deployment
Development tools: Individuals who can use common development tools such as Git/GitHub, containers (Docker, Kubernetes), CI/CD, and can build and operate machine learning pipelines, and manage experiments using MLflow and Kubeflow.
Understand algorithms, basic algorithms such as regression, classification, and time series, and be able to create, select, and tune models. Experience in deep learning-related development (over 1 year)
Someone capable of scratch implementation using frameworks such as PyTorch, TensorFlow, or Keras.
Experience in image recognition, multimodal models, or optimization and reinforcement learning implementations is a plus.
People who can utilize LLM-based libraries. Hugging Face, OpenAI, LangChain, and others
Experience in prompt engineering and RAG implementation
Infrastructure-related: The above environments can be built and implemented on cloud environments such as AWS, Azure, and GCP.
・Basic knowledge of artificial intelligence and information processing (graduate school level)
-
- Preferred
Must possess one of the following knowledge/experience
・Be well-versed
in the latest research fields related to machine learning/AI technologies ・Experience in AD/ADAS product development
・Experience in Cockpit product development
・Experience
in automotive electronic platform development
・Development experience in the automotive industry
-
- Location
- Tokyo, Aichi
-
- Work Style
- Remote working possible, Flex working possible
-
- Salary
- ¥9,000,000～¥14,300,000
-
- Attractive
Points - Japanese company with global opportunities, Listed company, Childcare support system, Weekends and holidays off, Major corporation
- Attractive
Consultation
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- In-Vehicle AI Technology Development AI Engineer