About GroundedAI
GroundedAI builds software systems that turn complex real-world data into reliable insights. Our products operate in challenging industrial environments where correctness performance and maintainability matter just as much as innovation.
We work at the intersection of software engineering applied machine learning and geospatial data. Our focus is on shipping robust systems not prototypes or research demos.
Role Overview
Were looking for a Software Engineer to join our core product engineering team. This role is ideal for someone with 5 years of experience who enjoys building and owning production systems end-to-end including services that incorporate machine learning and computer vision components.
Youll collaborate with engineers across the stack to design build deploy and operate software that includes ML-powered features while maintaining high standards for reliability performance and code quality.
This is a software engineering role first with machine learning as an important (but not exclusive) part of the problem space.
What Youll Do
- Design implement and maintain production software systems that power GroundedAIs products
- Build backend services and pipelines that support data processing model training and inference
- Integrate computer vision and ML components into user-facing applications
- Improve system performance reliability and observability in production environments
- Collaborate with product ML and frontend engineers to deliver end-to-end features
- Debug and resolve complex production issues across services data and infrastructure
- Contribute to technical design discussions and help evolve engineering best practices
What Were Looking For
Required
- 5 years of professional experience as a software engineer (backend platform or product)
- Strong fundamentals in software design debugging testing and code quality
- Experience building and operating production systems used by real users
- Proficiency in Python and experience with modern development workflows (Git CI/CD)
- Comfort working with APIs services and data pipelines
- Experience deploying software using Docker and cloud infrastructure (AWS GCP or Azure)
- Ability to collaborate across disciplines and take ownership of technical problems
ML / CV Experience (Nice to Have Not Required)
- Experience working with ML-backed or data-driven systems in production
- Familiarity with computer vision concepts such as image segmentation feature extraction or object detection
- Exposure to ML frameworks like PyTorch or TensorFlow
- Experience working with large datasets geospatial data or 3D / point-cloud data
Why GroundedAI
- Work on real-world systems with meaningful constraints and impact
- Strong engineering culture focused on ownership pragmatism and quality
- Opportunity to influence core architecture and technical direction
- Competitive compensation and benefits
- Flexible hybrid / remote work options
- Support for learning experimentation and professional growth
About GroundedAIGroundedAI builds software systems that turn complex real-world data into reliable insights. Our products operate in challenging industrial environments where correctness performance and maintainability matter just as much as innovation.We work at the intersection of software enginee...
About GroundedAI
GroundedAI builds software systems that turn complex real-world data into reliable insights. Our products operate in challenging industrial environments where correctness performance and maintainability matter just as much as innovation.
We work at the intersection of software engineering applied machine learning and geospatial data. Our focus is on shipping robust systems not prototypes or research demos.
Role Overview
Were looking for a Software Engineer to join our core product engineering team. This role is ideal for someone with 5 years of experience who enjoys building and owning production systems end-to-end including services that incorporate machine learning and computer vision components.
Youll collaborate with engineers across the stack to design build deploy and operate software that includes ML-powered features while maintaining high standards for reliability performance and code quality.
This is a software engineering role first with machine learning as an important (but not exclusive) part of the problem space.
What Youll Do
- Design implement and maintain production software systems that power GroundedAIs products
- Build backend services and pipelines that support data processing model training and inference
- Integrate computer vision and ML components into user-facing applications
- Improve system performance reliability and observability in production environments
- Collaborate with product ML and frontend engineers to deliver end-to-end features
- Debug and resolve complex production issues across services data and infrastructure
- Contribute to technical design discussions and help evolve engineering best practices
What Were Looking For
Required
- 5 years of professional experience as a software engineer (backend platform or product)
- Strong fundamentals in software design debugging testing and code quality
- Experience building and operating production systems used by real users
- Proficiency in Python and experience with modern development workflows (Git CI/CD)
- Comfort working with APIs services and data pipelines
- Experience deploying software using Docker and cloud infrastructure (AWS GCP or Azure)
- Ability to collaborate across disciplines and take ownership of technical problems
ML / CV Experience (Nice to Have Not Required)
- Experience working with ML-backed or data-driven systems in production
- Familiarity with computer vision concepts such as image segmentation feature extraction or object detection
- Exposure to ML frameworks like PyTorch or TensorFlow
- Experience working with large datasets geospatial data or 3D / point-cloud data
Why GroundedAI
- Work on real-world systems with meaningful constraints and impact
- Strong engineering culture focused on ownership pragmatism and quality
- Opportunity to influence core architecture and technical direction
- Competitive compensation and benefits
- Flexible hybrid / remote work options
- Support for learning experimentation and professional growth
View more
View less