Cogent Labs is looking for a Junior 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
- BSc/BEng degree in computer science or related fields, or equivalent experience
- Experience using modern Python (FastAPI, Pytorch, Pytest)
- Experience using database systems (SQL or NoSQL)
- 1+ years of professional experience
- 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.
About the Company
Cogent Labs ("Cogent") is a technology-driven, fast-paced AI SaaS company, and its mission is ambitious: “Power Productivity with Artificial Intelligence. We Empower Knowledge Workers.”
Cogent Labs provides products that improve knowledge worker productivity by leveraging cutting-edge AI technology. Our main product is the Intelligent Document Processing service "Smart Read" and it is a part of the integrated DX platform "COGENT DX".
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.