Recruit Detail
Find out more about the work we do, the experience and skills we can bring to the table, and our terms and conditions.
Company Name
Preferred Networks, Inc.
Job Type
Machine Learning, Optimization, and Data Science Engineer
Work Detail
We are recruiting engineers in the fields of machine learning, optimization, and data science year-round. We collaborate with client companies across diverse industrial sectors to solve challenges and realize PFN's vision of "making the real world computable" through research and development and implementation using our own supercomputers. We aim to provide high-value solutions that only PFN can offer, by learning specialized knowledge in each business domain and utilizing a broad range of computer science knowledge and implementation skills. We seek individuals who can actively communicate with people from diverse backgrounds, both inside and outside the company, and who can continuously learn new knowledge in line with PFN's "Learn or Die" values, thereby creating new value. The following are examples of work; however, actual work is not limited to these. The projects and tasks you will actually be responsible for after joining the company will be determined based on your specialized knowledge and experience. **Examples of Work** As an engineer, you will manage and promote projects for problem-solving, including new projects. - Launching new projects, conducting customer interviews, defining requirements, engineering, and reporting. - Observation and analysis of data related to existing equipment and processes, as well as their operation and management. - Defining tasks suitable for resolution using machine learning techniques and satisfying customer needs. - Establishing and implementing evaluation methods for machine learning model operation and application behavior based on actual equipment, data, or simulations, and conducting technical verification using these methods. - Explaining machine learning model operation and control behavior to customers and users, and developing, implementing, and verifying technical methods to enhance explainability (such as visualization). - Providing technical advice to engineers at client companies. We provide problem-solving services such as time series forecasting, mathematical optimization, and inverse problem analysis, depending on the problem domain and the client's business domain. - Construction and verification of machine learning models for prediction or anomaly detection of time-series data related to target equipment and processes. - Proposal, implementation, and experimentation of solutions to real-world combinatorial optimization problems from a multifaceted perspective including heuristics, mathematical programming, and machine learning. - Inverse problem analysis and estimation of the internal state and structure of measured objects using real-world remote sensing data. - Domain adaptation of simulation data and real-world data. We develop technologies to control large-scale production facilities such as chemical plants in operation, as well as industrial machinery and robotic equipment, to enable safer and more optimal operation. - Construction of machine learning models that enable optimal control while guaranteeing safety. - Construction of machine learning models that detect and predict equipment anomalies using time-series operating data. We develop technologies for efficient manufacturing, utilizing simulations and other methods, for manufacturing processes and equipment. - Formulating problems using 2D/3D particle simulations and applying them to machine learning - Development of continuous and discrete optimization algorithms for exploring optimal manufacturing processes - Construction and operation of a system that performs optimization processing using developed algorithms and machine learning models in conjunction with our own cluster We propose data analysis and problem-solving solutions that lead to improved profitability and customer satisfaction in the retail industry. We develop methods that contribute to the restructuring of operations and improvement of operational quality in the retail industry. - Problem setting and hypothesis building through observation of store operations and discussions with stakeholders - Leading the construction of data collection and analysis infrastructure in collaboration with other internal teams and client companies - Development of image and POS data analysis and optimization methods for the purpose of sales promotion, avoiding lost opportunities, and inventory optimization - Verification of the effectiveness of development methods in collaboration with client companies
Ideal Profile
Application Requirements (Required) - Experience in problem-solving utilizing computer science knowledge - A commitment to mastering all areas of computer science and constantly pursuing cutting-edge technologies - In particular, research or practical experience and achievements in machine learning - Experience in problem-solving based on real data - In particular, the ability to define appropriate tasks that satisfy customers and are technically solvable - Software development experience (Python, Go, C, C++, Java, etc.) - Understanding of computer architecture and the ability to create programs that are mindful of software execution efficiency and computational complexity - Programming ability, especially in Python or C++ - Practical experience in several of the following areas: - Application development or operation experience - Regardless of the device (Web/client/smartphone, etc.) - Regardless of genre (tools/games, etc.) - Library development experience - Unix/Linux server operation experience - High school level knowledge of mathematics and natural sciences (physics, chemistry, etc.) (or the ability to acquire this knowledge through study) - Experience in team problem-solving - Business-level Japanese proficiency (for non-native Japanese speakers, JLPT N1 level) (Skill Level Equivalent) Qualifications (Preferred) - Proficiency in all areas of computer science - Software development experience - Experience leading development projects as a lead engineer - Experience contributing to open-source software (OSS) - Experience developing systems using cloud services such as AWS and GCP - Experience building CI/CD systems - Experience managing infrastructure using Terraform, Ansible, etc. - Demonstration of outstanding programming/hardware design skills - Data analysis skills and experience applying computer science knowledge - Data analysis techniques using machine learning and statistical tools (e.g., NumPy / pandas / scikit-learn; proficiency in specific tools is not required) - Achievements and experience in programming competitions, game AI competitions, data analysis competitions (e.g., Kaggle) - University-level knowledge of mathematics, physics, and chemistry - Specialized knowledge, experience, or achievements in any of the following industrial or academic fields: - Chemical plants and chemical engineering - Machine tools and manufacturing - Continuum mechanics - Other industrial or academic fields - Expert knowledge, experience, or track record in various data, numerical calculation, and analysis methods: - Mathematical optimization (continuous optimization, discrete optimization, combinatorial optimization, etc.) - High-dimensional data and big data processing - Domain gap resolution (Sim2real, Domain adaptation, data assimilation, etc.) - Time series data analysis (e.g., sensor data) - Signal processing and computer vision - Physical numerical simulation - Research and development experience - Deep knowledge and experience in one's specialized field - Experience researching, reading, and creating survey materials for English academic papers - Experience writing academic papers in English - Project management and leadership experience - Experience leading teams of 10 or more people - Experience managing projects in collaboration with external clients, etc.
Work Location
Otemachi Bldg., 1-6-1 Otemachi, Chiyoda-ku, Tokyo, Japan 100-0004 Remote work system available (limited to work in Japan)
Phd. Stating Salary
Compensation will be determined based on experience, performance, abilities, and contributions, in accordance with company regulations.