About the Role
The role involves developing and maintaining AI-driven solutions, integrating machine learning models into production environments, and working closely with cross-functional teams to deliver robust, scalable systems.
Responsibilities
- Design and deploy artificial intelligence models tailored to specific use cases
- Optimize system performance for low latency and high availability
- Integrate AI components with backend services and data pipelines
- Monitor and troubleshoot live AI systems to ensure reliability
- Collaborate with data scientists to transition prototypes into production
- Implement model versioning and lifecycle management practices
- Ensure compliance with data privacy and security standards
- Develop APIs and interfaces for AI functionality access
- Support infrastructure automation for AI workloads
- Conduct code reviews and contribute to system architecture decisions
- Maintain documentation for AI systems and integration points
- Evaluate emerging AI technologies for potential adoption
- Participate in incident response related to AI service disruptions
- Work with operations teams to streamline deployment processes
- Contribute to capacity planning for AI model hosting
Nice to Have
- Master’s degree in computer science or AI-related discipline
- Experience with large language models or transformer architectures
- Familiarity with MLOps tools like MLflow or Kubeflow
- Hands-on experience with edge AI deployment
- Knowledge of reinforcement learning applications
- Prior work in high-throughput, low-latency environments
- Contributions to open-source AI projects
- Experience with model explainability and fairness tools
- Background in cybersecurity as it applies to AI systems
- Exposure to real-time data streaming platforms
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexible scheduling
Team
Collaborative team environment focused on innovation and technical excellence
Technology Stack
- Primary languages include Python and JavaScript
- Infrastructure built on Kubernetes with cloud orchestration
- Models developed using PyTorch and TensorFlow
- CI/CD pipelines powered by Jenkins and GitHub Actions
- Data storage via PostgreSQL and BigQuery
- Monitoring through Prometheus and Grafana
- Authentication and access managed through OAuth2 and IAM roles
Professional Development
- Annual learning budget for courses and certifications
- Access to AI research publications and conference attendance
- Internal tech talks and knowledge-sharing sessions
- Mentorship programs for career advancement
- Opportunities to publish technical work
Work Environment
- Modern office space with collaborative zones
- Ergonomic workstations and remote setup support
- Flexible hours with core collaboration windows
- Pet-friendly office policy
- Onsite and virtual wellness programs
Diversity and Inclusion
- Commitment to building an inclusive workplace
- Employee resource groups for underrepresented communities
- Bias training for hiring managers
- Equitable promotion practices
- Anonymous feedback channels
Sustainability Initiatives
- Carbon footprint tracking for AI training runs
- Green cloud computing practices
- Remote-first policy to reduce commuting impact
- Sustainable office supplies and waste reduction
- Partnerships with environmental nonprofits
Available for qualified candidates
