About the Role
Develop efficient machine learning models and collaborate across engineering teams to integrate AI solutions into hardware and software platforms.
Responsibilities
- Design and implement scalable machine learning algorithms
- Optimize models for deployment on edge devices
- Collaborate with cross-functional teams to integrate AI capabilities
- Evaluate model performance using quantitative metrics
- Improve inference speed and reduce computational overhead
- Develop training pipelines for supervised and unsupervised learning
- Maintain documentation for model architecture and training processes
- Troubleshoot issues in model deployment and operation
- Stay current with advancements in AI and deep learning
- Support testing and validation of AI-driven features
- Work closely with software engineers to ensure seamless integration
- Contribute to research initiatives in model efficiency
- Apply techniques for model compression and quantization
- Ensure models meet accuracy and latency requirements
- Participate in code and design reviews
- Use version control systems for model and code management
- Assist in defining technical requirements for AI projects
- Monitor model behavior in production environments
- Implement solutions for data preprocessing and augmentation
- Support deployment across multiple hardware platforms
- Analyze large datasets to inform model design
- Develop strategies for handling imbalanced or noisy data
- Conduct experiments to validate model improvements
- Ensure compliance with internal technical standards
- Communicate technical findings to non-specialist stakeholders
Nice to Have
- Master's degree in a technical discipline
- Experience with model quantization and pruning
- Knowledge of on-device AI frameworks
- Background in computer vision or NLP
- Publication record in machine learning venues
- Hands-on experience with hardware-software co-design
- Familiarity with automated machine learning tools
- Experience optimizing models for low-power devices
- Contributions to open-source machine learning projects
- Understanding of model security and robustness
Compensation
Competitive salary with benefits package
Work Arrangement
Hybrid work model available
Team
Innovative R&D environment focused on advanced technology development
About the Team
Work within a forward-thinking research and development unit focused on integrating artificial intelligence into consumer electronics and advanced systems.
Technology Stack
Utilize Python, PyTorch, TensorFlow, ONNX, TensorRT, Git, Linux, and cloud platforms for model development and deployment.
Available for qualified candidates
