About the Role
Design and build robust, scalable platforms that power AI and machine learning applications. Maintain system reliability, optimize performance, and support integration across services.
Responsibilities
- Develop core infrastructure for AI-driven applications
- Ensure platform scalability and system reliability
- Collaborate with data scientists and ML engineers
- Optimize distributed computing environments
- Implement monitoring and observability tools
- Maintain security and compliance standards
- Support deployment pipelines and CI/CD workflows
- Troubleshoot production issues promptly
- Integrate third-party AI services and APIs
- Write clean, maintainable, and well-documented code
- Participate in architectural design discussions
- Evaluate and adopt new technologies strategically
- Improve system performance and latency
- Manage containerized environments using Kubernetes
- Work with large-scale data processing frameworks
- Ensure efficient resource utilization across clusters
- Support model deployment and lifecycle management
- Contribute to internal tooling and automation
- Collaborate on incident response and on-call rotations
- Drive best practices in software engineering and operations
Nice to Have
- Master's degree in Computer Science or related area
- Experience with MLOps platforms
- Familiarity with TensorFlow or PyTorch
- Contributions to open-source projects
- Background in high-performance computing
- Knowledge of model serving frameworks
- Experience with feature stores or data pipelines
- Exposure to edge AI deployment
- Security-first mindset in system design
- Leadership in technical project planning
Compensation
Competitive salary with equity and benefits package
Work Arrangement
Hybrid remote with office options
Team
Collaborative engineering team focused on AI and platform development
About the Role
This position focuses on building the backbone of AI-powered systems, enabling efficient model training, deployment, and inference at scale. The engineer will work closely with research and product teams to translate experimental models into production-grade services.
What We Value
Technical excellence, clear communication, ownership of systems, and a drive to solve hard infrastructure problems. We value candidates who balance innovation with operational discipline.
Available for qualified candidates
