Data Scientist, Perception
Tokyo
Woven by Toyota
Woven by Toyota will help Toyota to develop next-generation cars and to realize a mobility society in which everyone can move freely, happily and safely.=========================================================================
TEAMWe develop human-centered automated driving solutions for personal and commercial use. We develop perception technologies and its production software for the AD/ADAS system. To work towards a reliable and functional system, we are solving complex real-world problems using large-scale data, machine learning algorithms, and a variety of perception technologies.
WHO ARE WE LOOKING FORYou will combine modern technologies with safety standards while also considering cost efficiency. You will be an expert in neural networks and software engineering. Also, you have patience to handle the processes required for production development and approach them by asking "What can I do for you?" with a "Giver" mindset.
You appreciate a hybrid workspace and can come to our Nihonbashi office three days per week, and report to the head of perception engineering for ADADAS.
RESPONSIBILITIES
- Come up with data strategies on how to collect, sample, label, handle, and use tons of data from the market, test vehicles, and simulators to improve machine learning model performance of the perception stack for camera images that is deployed to millions of vehicles.
- Design and improve the scalable data pipelines and automation for machine learning and performance evaluation
- Analyze large-scale data and identify its characteristics to propose technical solutions for machine learning and performance evaluation
- Lead data-related activities within the team, across the company in collaboration with Toyota group, and enhancing team members' capability for data science.
MINIMUM QUALIFICATIONS
- Bachelor's degree in science or engineering
- 1+ years experience in data science or related areas
- Experience with theoretical aspects of data science like machine learning (deep learning, statistical analysis, and mathematical modeling)
- Experience writing software in Python for data science (numpy, scipy, scikit, pandas), using SQL (or another type) database, and AWS services
- Business-level proficiency in English
NICE TO HAVES
- Master's degree or Ph.D. in related field
- 5+ years experience in data science or related areas
- 2+ years tech lead or management experience in data science or related areas for business applications, such as production, commercial service or public service development
- Hands-on experience in the following:
- Analyze huge (e.g. peta byte) scale database
- Develop perception-related technologies, such as camera image processing, computer vision, machine learning, or deep learning
- Design data annotation rules for machine learning
- Build or manage infrastructure, such as Docker, Kubernetes, Jenkins, GitHub Actions
- Work in the automotive industry (especially, AD/ADAS field
- Business-level proficiency in Japanese (especially, smooth reading and listening)
WHAT WE OFFER・Competitive Salary - Based on experience・Work Hours - Flexible working time・Paid Holiday - 20 days per year (prorated)・Sick Leave - 6 days per year (prorated)・Holiday - Sat & Sun, Japanese National Holidays, and other days defined by our company・Japanese Social Insurance - Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance・Housing Allowance・Retirement Benefits・Rental Cars Support・In-house Training Program (software study/language study)
Our Commitment・We are an equal opportunity employer and value diversity.・Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Computer Vision Data pipelines Deep Learning Docker Engineering GitHub Jenkins Kubernetes Machine Learning NumPy Pandas Pipelines Privacy Python Scikit-learn SciPy SQL Statistics
Perks/benefits: Career development Competitive pay Flex hours Health care
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