👋 About the Team
The EdgeFM team is responsible for enhancing the performance of EdgeFM-Engine, a core module of NVA (Nota Vision Agent) — the flagship product in Nota’s AI-based solution business. We focus on developing the inference modules of Large Vision-Language Models, while improving overall inference performance through hardware-specific optimization and model lightweighting. At the forefront of the rapidly evolving Foundation Model field, we continuously adopt new technologies and explore innovative ways to meet real-world industrial demands. This environment offers engineers the opportunity to gain deep, hands-on experience and technical expertise as AI researchers and developers.
📌 What You’ll Do at This Position
The EdgeFM team develops and operates the EFM-Engine, the core component and final output of the NVA solution. You will ensure the stable delivery of advanced research results through device compatibility management, CI/CD verification pipelines, and bug resolution, while building and maintaining benchmark pipelines and monitoring systems to validate the engine’s reliability with objective data and contribute to the team’s overall goals.
✅ Key Responsibilities
- Ensure the reliability and stability of the EFM-Engine
- Establish and manage Engine compatibility across diverse deployment environments (Devices)
- Develop Monitoring Metrics and design tests to ensure the Observability of the EFM-Engine
- Build and manage the CI/CD pipeline
- Analyze Engine bugs and provide technical support
- Manage internal development tools
- Build and manage EFM-Engine performance evaluation and simulation pipelines using workflow management tools such as Airflow
- Maintain software tools used to support EFM-Engine development and usage
✅ Requirements
- 3+ years of practical experience in a related field.
- Proficient in Python and possesses a strong foundation in computer science (Data Structures, Algorithms, etc.).
- Deep understanding and hands-on experience with Docker container technology.
- Experience building and operating CI/CD pipelines.
- Experience building and operating MLOps pipelines (e.g., using MLFlow, Airflow).
- Familiarity with Git for version control and collaborative development.
- Clear communication skills for seamless collaboration and the ability to proactively solve problems.
✅ Pluses
- Experience in large-scale service backend development.
- 1+ year of experience in MLOps or DevOps engineering.
- Experience building and operating monitoring systems (e.g., Grafana, Prometheus).
- Experience with large-scale deployment, scaling, and management using Kubernetes.
- Experience developing data pipelines using workflow management tools (e.g., Airflow).
✅ Hiring Process
- Document Screening → Screening Interview → Assignment → 1st Interview → 2nd Interview
(Additional assignments may be included during the process.)
🤓 A Message from the Team
The EdgeFM team drives a wide range of R&D initiatives—from model optimization and lightweighting to specialized model development—to meet the speed and accuracy required in real-world applications. This work plays a key role in shaping the core value of our solutions, offering opportunities to gain direct and indirect experience with cutting-edge Foundation Model technologies and AI infrastructure.
If you aspire to grow as an AI software expert, you will find meaningful challenges and growth opportunities within the EdgeFM team.
Please Check Before Applying! 👀
- This job posting is open continuously, and it may close early upon completion of the hiring process.
- Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
- Providing false information in the submitted materials may result in the cancellation of the application.
- Please be aware that references will be checked before finalizing the hiring decision.
- Compensation will be discussed separately upon successful completion of the final interview.
- There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials
👋 About the Team
The EdgeFM team is responsible for enhancing the performance of EdgeFM-Engine, a core module of NVA (Nota Vision Agent) — the flagship product in Nota’s AI-based solution business. We focus on developing the inference modules of Large Vision-Language Models, while improving overall inference performance through hardware-specific optimization and model lightweighting. At the forefront of the rapidly evolving Foundation Model field, we continuously adopt new technologies and explore innovative ways to meet real-world industrial demands. This environment offers engineers the opportunity to gain deep, hands-on experience and technical expertise as AI researchers and developers.
📌 What You’ll Do at This Position
The EdgeFM team develops and operates the EFM-Engine, the core component and final output of the NVA solution. You will ensure the stable delivery of advanced research results through device compatibility management, CI/CD verification pipelines, and bug resolution, while building and maintaining benchmark pipelines and monitoring systems to validate the engine’s reliability with objective data and contribute to the team’s overall goals.
✅ Key Responsibilities
- Ensure the reliability and stability of the EFM-Engine
- Establish and manage Engine compatibility across diverse deployment environments (Devices)
- Develop Monitoring Metrics and design tests to ensure the Observability of the EFM-Engine
- Build and manage the CI/CD pipeline
- Analyze Engine bugs and provide technical support
- Manage internal development tools
- Build and manage EFM-Engine performance evaluation and simulation pipelines using workflow management tools such as Airflow
- Maintain software tools used to support EFM-Engine development and usage
✅ Requirements
- 3+ years of practical experience in a related field.
- Proficient in Python and possesses a strong foundation in computer science (Data Structures, Algorithms, etc.).
- Deep understanding and hands-on experience with Docker container technology.
- Experience building and operating CI/CD pipelines.
- Experience building and operating MLOps pipelines (e.g., using MLFlow, Airflow).
- Familiarity with Git for version control and collaborative development.
- Clear communication skills for seamless collaboration and the ability to proactively solve problems.
✅ Pluses
- Experience in large-scale service backend development.
- 1+ year of experience in MLOps or DevOps engineering.
- Experience building and operating monitoring systems (e.g., Grafana, Prometheus).
- Experience with large-scale deployment, scaling, and management using Kubernetes.
- Experience developing data pipelines using workflow management tools (e.g., Airflow).
✅ Hiring Process
- Document Screening → Screening Interview → Assignment → 1st Interview → 2nd Interview
(Additional assignments may be included during the process.)
🤓 A Message from the Team
The EdgeFM team drives a wide range of R&D initiatives—from model optimization and lightweighting to specialized model development—to meet the speed and accuracy required in real-world applications. This work plays a key role in shaping the core value of our solutions, offering opportunities to gain direct and indirect experience with cutting-edge Foundation Model technologies and AI infrastructure.
If you aspire to grow as an AI software expert, you will find meaningful challenges and growth opportunities within the EdgeFM team.
Please Check Before Applying! 👀
- This job posting is open continuously, and it may close early upon completion of the hiring process.
- Resumes that include sensitive personal information, such as salary details, may be excluded from the review process.
- Providing false information in the submitted materials may result in the cancellation of the application.
- Please be aware that references will be checked before finalizing the hiring decision.
- Compensation will be discussed separately upon successful completion of the final interview.
- There will be a probationary period after joining, and there will be no discrimination in the treatment during this period.
- Veterans and individuals with disabilities will receive preferential treatment in accordance with relevant regulations.
🔎 Helpful materials