LeapMind is mainly engaged in the research and development of quantized neural networks and the development of Efficiera, an accelerator to run such networks at high speed, in order to solve the problem of power consumption, which is a major barrier to the widespread use of deep learning. Due to the fact that we develop our own hardware, we are looking for a machine learning engineer who is proficient in deep learning and can lead projects that utilize it in order to develop models that run at high efficiency while meeting the limitations of our hardware.
In particular, we are looking for a talented machine learning engineer who can develop highly practical deep learning models to realize edge AI that works in various industrial fields that require low-power devices, utilizing Efficiera.
- Development of quantized deep learning models considering embedded environments that run efficiently on our accelerator IP, Efficiera
- Develop high performance, high quality models that meet business and customer requirements in target industries
- Create product specifications, overall design, development plans, and lead design and development projects
- Researching, understanding and sharing the latest technology trends
- Master's degree in informatics or a nearby field, or equivalent knowledge and experience
- Experience (1+ years) leading the design and development of a product or system development project using machine learning or deep learning frameworks in a multi-person team
- Experience (2+ years) as a developer designing, developing, and researching systems and products using deep learning
- Deep understanding of image processing and computer vision and practical experience using it (2+ years)
- Experience in software development projects based on Agile or Scrum development (2+ years)
- Business level communication skills in Japanese
Nice to Have
- PhD or equivalent knowledge and experience in informatics or a neighboring field.
- Experience developing products and solutions that combine image processing and computer vision with deep learning models
- Understanding of computer architecture and low-level programming experience
- Experience with various model compilers and runtimes for deep learning. (TensorRT, TensorFlow Lite, OpenVINO, ONNX Runtime, etc.)
- Experience optimizing machine learning or deep learning models for embedded devices
- Experience in accepting peer-reviewed papers on machine learning and deep learning
- Experience with machine learning competitions (e.g. Kaggle), competitive programming. (e.g. AtCoder)
- Experience bringing products to market
- You share LeapMind's mission and vision (https://leapmind.io/about/) and are committed to developing products that solve customer issues
- Able to lead a company-wide project from start-up to closing, with appropriate support from others, using good judgment to lead the project autonomously to a successful conclusion
- A team player and able to communicate with others in a respectful manner
- Able to build consensus through constructive dialogue and discussion based on trust and cooperation in order to produce optimal outputs efficiently and effectively
- Able to extract issues from facts and events, prepare documents (proposals) that clarify goals, issues, and the best means of addressing them, and explain them to relevant parties regardless of position (we emphasize documentation when sharing information in order to ensure transparency and prevent information asymmetry)
- Share our mission and vision and take on challenges toward the same future
- Development language: Python, C++
- OS: Linux
- ML Libraries: TensorFlow, PyTorch, scikit-learn
- Other: GitHub Enterprise, Slack
- Company profile: https://leapmind.io/careers/
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About the Company
LeapMind Inc. is developing its business with the company mission, “to create innovative devices with machine learning and make them available everywhere” and our original weight reduction technology for deep learning models, the dedicated circuit design, and leveraging the knowledge gained from the collaboration with more than 150 companies.
Our core product "Efficiera" is an ultra-low power AI inference accelerator that can be implemented on an FPGA device or ASIC/ASSP device, and is specialized for CNN inference operations, taking full advantage of our original deep learning model weight reduction method "extremely low bit quantization". It will enable advanced data processing by deep learning in environments where AI could not be used before.
Full time (No fixed period)
3 months（under same condition）
Based on one's experience, ability, and previous salary
Bonus to be paid twice annually based on company performance
The amount will be paid according to the commuting route approved by the company. However, actual expenses will be reimbursed according to the number of days coming to the office. (Monthly limit: the lesser of the monthly commuting fee or 50,000 yen)
Flex-time system (5:00~22:00, Standard working hours: 8h/day), no core time
Employees' Pension Insurance, Health Insurance, Employment Insurance
Regular medical check-ups etc.
Allowance for Working from Home 5K yen per month