Synspective provides solutions for customers’ challenges with utilizing and integrating data from Synthetic Aperture Radar (“SAR”) satellite constellations, big data, and machine learning. We use English internally, so no Japanese is required for our software engineering positions.
Our core values
Fairness. Respect each member’s lifestyle, experiences, culture and mission. Be honest to data. Appreciate counter opinions and feedback.
Efficency. Time is the most important resource. We, as one team, aim to achieve the best results in the shortest time. Take a control of your time and be responsible for your performance. Make recurring tasks automated. Focus on selected fields to maximize work value in the shortest time possible.
Proactiveness. Proactively identify problems and act immediately. Never be afraid to fail. Be candid and ask team for help whenever needed.
Collective Intelligence. Individual growth leads to team growth. Keep learning and share with the team. Be social and expand your network. Use external resources as necessary
Full-time (Nontenured). All members are contract-based employees. The contract is renewed in every six months based on management by objective to assist individual growth and team growth
- Commuting expense, health insurance, employees’ pension insurance.
- Flexible work-hours and location
- Part-time or second job allowed
Our response to COVID-19
Our business hasn’t been directly impacted by COVID-19. During the crisis, we’ve switched to having all employees work fully remotely. We do not have any concrete plans yet about going back to the office, but will follow the government’s policy.
Since the travel restrictions have been lifted, we are open to overseas candidates who are exceptional matches.
About the position
- Research and develop innovative geo-solutions, including:
- Deeply investigate the latest advances in relevant fields (machine learning, computer vision, and remote sensing) and design your own methods by handpicking, customizing, combining, or devising algorithms
- Choose, combine, and process appropriate satellite/geographic datasets depending on tasks
- Perform experiments to check the feasibility/validity of your own methods and dataset
- Summarize and report results in a clear and easy-to-understand manner
- Implement statistical and machine learning technologies and help software engineers deploy them into production
- Proactively find research themes and address them
- Partner closely with business staff and judge the feasibility of potential business ideas based on your technical knowledge before they are put into practice
- Continuously improve you and your team’s skills
- 3+ years of practical experience in applying machine learning, computer vision, image processing, or related fields of technologies to solve real-world problems
- Strong knowledge and implementation skill of statistics and machine learning algorithms
- 3+ years of hands-on experience with Linux, Python, and scientific Python ecosystem (NumPy, Pandas, Jupyter, and so forth)
- Experience with deep learning frameworks (TensorFlow, PyTorch, and so forth) to run experimental workflows
- Ability to read academic papers without difficulty and select, combine, and implement technical approaches to solve problems
- Motivation to learn new things and share them with the team
- Good oral and written communication skills in English to convey techniques and results of analyses concisely to both experts and non-experts
- Master’s degree or Ph.D. in computer science, statistics, machine learning, applied math, data science, or equivalent field
- Experience in implementing your own algorithm and deploying it into production
- Publications at peer-reviewed conferences or journals
- Experience in reproducing papers
- Experience with Docker and GCP
- Experience in handling satellite images or GIS data
- Knowledge of the generation process of electro-optical or SAR satellite imagery
- Knowledge of characteristics of many different satellite image products