About the Role
The role involves leading the development of AI-driven features, from concept to deployment, with ownership over model architecture, data pipelines, and system integration within a fast-moving product environment.
Responsibilities
- Design scalable machine learning models for production environments
- Optimize data processing workflows for training and inference
- Collaborate with software engineers to embed AI capabilities
- Evaluate model performance using statistical and business metrics
- Maintain documentation for model development and deployment
- Troubleshoot issues in AI pipelines and resolve system bottlenecks
- Stay current with advancements in artificial intelligence research
- Implement security practices in model training and deployment
- Work with product teams to define AI use cases
- Ensure compliance with data governance standards
- Refactor legacy systems to support intelligent automation
- Lead code reviews for machine learning components
- Monitor system behavior post-deployment
- Contribute to architectural decisions for AI infrastructure
- Support testing frameworks for model validation
- Integrate third-party AI tools when appropriate
- Develop APIs for model access and interaction
- Manage versioning for models and datasets
- Coordinate with data scientists on feature engineering
- Drive best practices in reproducible experimentation
- Optimize resource usage in cloud-based environments
- Assist in defining project timelines and milestones
- Mentor junior engineers in AI techniques
- Participate in technical planning sessions
- Ensure ethical considerations in AI design
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid remote setup with team collaboration flexibility
Team
Collaborative engineering group focused on innovation and technical excellence
Tech Stack
Python, PyTorch, TensorFlow, FastAPI, Docker, Kubernetes, PostgreSQL, GCP, Airflow, Prometheus
Culture & Values
- We prioritize technical rigor, open communication, and continuous learning
- Team members are encouraged to propose and lead initiatives
- Collaboration across disciplines is central to our workflow
- We value sustainable development practices and thoughtful iteration
Growth Opportunities
- Access to conferences and training programs
- Internal mobility across technical tracks
- Regular feedback and career development discussions
- Mentorship from experienced AI practitioners
Available for qualified candidates
