Founded in 2014, Cogent Labs is devoted to providing innovative solutions to real-world problems in order to improve people’s quality of work and life through intelligent automation.
We believe achieving this goal requires a deep understanding of customers' needs and practices in order to build products that can leverage the power of custom AI models through a carefully crafted UI and UX. Our main product is SmartRead, a generic and versatile solution for automating digital and analog document processing for a wide range of businesses.
Headquartered in Tokyo, we are a diverse company with international members from 20 different countries. We are looking for exceptional talent with deep domain expertise that are eager to work with our team on crafting and delivering unique value to our customers.
What we offer
- Competitive Salary - Based on skills and experience.
- Performance bonus eligibility twice a year.
- Work Hours - Standard work hours 9:00 -18:00 with flexible time system around core hours.
- Telework Policy - 6 days / month.
- Paid Holiday - Maximum 20 days per year (additional Congratulatory, Bereavement leaves available).
- Holiday - Sat & Sun, Japanese National Holidays, and Year-end and New Year holidays.
- Visa Sponsorship.
- Support for language training.
- Free in-office breakfast, coffee, tea, drinks and snacks.
- Subsidized gym membership.
- Monthly commute expense.
- Japanese Social Security - all applicable (Health Insurance, Pension, employment insurance etc.).
- Maternity leave, childcare leave (including male employees).
- Yearly health checkup.
Cogent Labs is looking for a Machine Learning Engineer to help accelerate how we create and deploy machine-learning-based solutions to real-world business problems.
Successful candidates will join a highly-skilled and growing team of ML engineers and scientists, using modern software engineering techniques, coding practices, and technologies. The team combines data engineering, machine learning engineering, and devops engineering practices, providing a great opportunity for learning and growth.
- Developing and maintaining AI model training pipelines and experiment tracking.
- Collaborating with machine learning scientists to bring research findings to production.
- Deployment and maintenance of AI models in production.
- Maintaining training dataset management systems.
Qualifications and skills
- BSc/BEng degree in computer science or related fields, or equivalent experience.
- 3+ years of professional experience.
- Experience using modern Python (FastAPI, Pytorch, Pytest).
- Experience using database systems (SQL or NoSQL).
- Familiarity with software containerization (Docker and Kubernetes).
- Experience building training pipelines and productionizing AI models.
- Experience building ETL data pipelines.
- Knowledge of Japanese language.
We are working in a dynamic environment, using modern technologies such as PyTorch, Docker, Knative, Kafka, Kubernetes, Nvidia Triton, Github Actions, and cloud platforms such as Google Cloud Platform and Amazon Web Services.
The Cogent Labs engineering department is continuously working towards developing a culture improving and rewarding the following qualities:
- Team effort: A cohesive team can be more effective than an isolated prodigy. Engineers are expected to work well in groups and look for opportunities to empower their colleagues.
- Ownership: Take full responsibility for your own projects and tasks and if needed, cross over boundaries in order to successfully deliver your project.
- Self-improvement: Create an environment where engineers can focus on their engineering tasks and self-improvement without excessive outside disturbances.
- Experimentation: Engineers should have some freedom in experimenting with new ideas and technologies, as this ultimately could translate into building better products or the creation of valuable new IP.
- Quality & Excellence: Maintaining a mindset of developing high quality features and code. We avoid cutting corners as much as possible.
- Customer Service: Being customer focused, not only externally but internally as well. This means developing services that not only improve the experience of our end customers, but also being ‘customer service’ oriented within your team and the company as a whole by helping out others and sharing knowledge.