About the Role
The role involves developing, testing, and implementing artificial intelligence models to meet technical and business requirements while working closely with cross-functional teams.
Responsibilities
- Design machine learning models for scalable applications
- Develop data pipelines to support AI training and inference
- Collaborate with software engineers to integrate AI components
- Optimize model performance and computational efficiency
- Evaluate AI outputs against defined success metrics
- Maintain documentation for model development and deployment
- Troubleshoot issues in AI-driven systems
- Stay current with advancements in artificial intelligence
- Apply ethical standards to model design and deployment
- Work with product teams to define AI use cases
- Conduct experiments to validate model accuracy
- Refine algorithms based on feedback and testing
- Support deployment of AI models into production environments
- Monitor system behavior post-deployment
- Participate in code reviews and technical discussions
- Ensure compliance with data privacy regulations
- Use version control for model and code management
- Assist in defining infrastructure needs for AI workloads
- Contribute to technical planning and roadmap sessions
- Communicate technical concepts to non-technical stakeholders
- Implement security best practices in AI systems
- Assess risks associated with AI model decisions
- Support continuous integration and delivery pipelines
- Engage in peer learning and knowledge sharing
- Respond to system alerts related to AI functionality
Nice to Have
- PhD in a relevant technical discipline
- Prior experience deploying AI in production environments
- Background in reinforcement learning
- Experience with edge computing and AI on devices
- Contributions to open-source AI projects
- Published research in AI or machine learning
- Experience with MLOps tools and practices
- Knowledge of distributed computing frameworks
- Familiarity with data annotation workflows
- Experience working in regulated industries
Compensation
Competitive salary based on experience
Work Arrangement
Hybrid work model with flexible scheduling
Team
Collaborative team environment focused on innovation
Technology Stack
- Primary languages include Python and JavaScript
- Frameworks used are PyTorch, TensorFlow, and Hugging Face Transformers
- Cloud infrastructure hosted on Google Cloud Platform
- Container management via Docker and Kubernetes
- Data stored in BigQuery and Cloud Storage
- CI/CD pipelines powered by GitHub Actions
- Monitoring tools include Prometheus and Grafana
- Collaboration through Jira and Confluence
Growth Opportunities
- Access to conference attendance and training programs
- Internal mobility across technical and research roles
- Mentorship from senior AI practitioners
- Opportunities to lead project initiatives
- Support for publishing technical work
- Cross-team collaboration on experimental projects
Available for qualified candidates
