【グローバルエンジニアリングソリューション会社】ソフトウェアエンジニア - AI

案件ID 17987
勤務形態
正社員
給与
6,000,000 ~ 8,000,000 JPY per year + 20% Bonus + Health Insurance + Benefits + Holidays + Flexible Hours
日本語レベル
なし
英語レベル
ビジネスレベル(TOEIC 860)
開始日
ASAP
勤務地
東京
勤務形態
正社員
給与
6,000,000 ~ 8,000,000 JPY per year + 20% Bonus + Health Insurance + Benefits + Holidays + Flexible Hours
日本語レベル
なし
英語レベル
ビジネスレベル(TOEIC 860)
開始日
ASAP
勤務地
東京

職務内容

One of our Clients, an engineering services Organization that is spread in more than 70 locations worldwide, is looking for 3 talented Software Engineers - Artificial Intelligence for an ongoing project with their client.

This is an exciting opportunity for an Artificial Intelligence Software engineer / Senior Software Engineer with a proven track record in developing, training and validating AI/ML Models based on customer requirements.

 

Objective of this Role:

Design, Development, Training & Testing of AI Models for ADAS-AD platforms and related applications

 

KEY DUTIES & RESPONSIBILITIES:

- Collaborate closely with customer to capture the requirements & communicate that to offshore

- Design, Development/Port, Integration and Testing of AI-ML Models

- Review and ensure the quality of the design and source code of Self & Peers

- Complete the assigned tasks on time and ensure on time delivery and quality of the deliverable

 

 

【Company Details】

A leading global engineering solutions company that is always passionate about going the extra mile to provide new and possible engineering solutions for the clients.

【Working Hours】
9:00 - 18:00(Mon ‐ Fri)/Work environment: Hybrid (at office & WFH)

【Holidays】
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, Other Special Holidays
 
【Services / Benefits】

Social insurance, no smoking indoors allowed (Designated smoking area), transportation fees, etc.

 

必須スキル

- Experience of ADAS Embedded Application Development

- Ability to develop DL/ML models in Python, MATLAB, R etc

- Experience in devising, prototyping and testing machine-learning models

- Experience with standard DL tools and libraries like Caffe, Tensorflow, PyTorch, Keras, etc

- Good knowledge of deep learning (DL) concepts like CNN, FCN, LSTM etc

- Knowledge of network architectures for object detection, classification and semantic segmentation

- Experience in developing deep learning-based solutions in computer vision and imaging

- Knowledge of ML concepts for classification, regression, clustering, etc

- Analytical, problem solving and debugging skills