About the Role
The position involves translating AI research into scalable applications, working closely with engineering and product teams to integrate intelligent systems into existing workflows and ensure reliable, efficient performance.
Compensation
Competitive salary with performance-based incentives
Work Arrangement
Hybrid work model with flexible scheduling
Team
Collaborative environment focused on AI-driven solutions
Responsibilities
- Develop and refine machine learning models for practical deployment
- Collaborate with software engineers to integrate AI components into applications
- Evaluate model performance and implement improvements
- Translate business requirements into technical AI solutions
- Monitor deployed systems for accuracy and reliability
- Optimize AI pipelines for speed and resource efficiency
- Conduct testing to validate model outputs
- Maintain documentation for AI systems and workflows
- Stay current with advancements in applied machine learning
- Support the deployment of AI models across different platforms
- Troubleshoot issues in production environments
- Work with data scientists to refine training datasets
- Ensure models comply with ethical and operational standards
- Participate in design reviews and technical planning
- Assist in defining metrics for AI success
- Coordinate with stakeholders to gather feedback
- Implement security practices in AI development
- Contribute to version control and model tracking
- Support model retraining and updates
- Engage in knowledge sharing with team members
- Use programming tools for AI development and automation
- Apply statistical methods to improve predictions
- Design APIs for model access
- Work within agile development cycles
- Deliver scalable and maintainable code
Qualifications
- Bachelor's degree in computer science, engineering, or related field
- Minimum of three years in applied machine learning roles
- Experience with Python and common AI libraries
- Proficiency in cloud platforms such as AWS or GCP
- Strong understanding of model lifecycle management
- Hands-on experience with model deployment frameworks
- Familiarity with containerization tools like Docker
- Knowledge of CI/CD pipelines for AI systems
- Ability to work with structured and unstructured data
- Experience in debugging and optimizing models
- Solid grasp of data preprocessing techniques
- Background in software development best practices
- Understanding of neural networks and deep learning
- Skill in interpreting model behavior and outputs
- Experience with version control systems
- Ability to communicate technical concepts clearly
- Problem-solving orientation in real-world settings
- Track record of delivering AI projects on time
- Comfortable working in fast-paced environments
- Willingness to learn new tools and frameworks
- Experience with monitoring tools for AI systems
- Knowledge of data privacy principles
- Familiarity with MLOps concepts
- Ability to work independently and in teams
- Strong attention to detail in implementation
Preferred Qualifications
- Master's degree in a technical discipline
- Experience with natural language processing
- Background in computer vision applications
- Familiarity with large language models
- Knowledge of reinforcement learning
- Experience in regulated industries
- Exposure to edge computing for AI
- Track record of open-source contributions
- Published work in AI or machine learning
- Leadership in technical projects
- Experience mentoring junior developers
- Understanding of model explainability tools
- Work with time-series data
- Knowledge of transfer learning techniques
- Experience in high-availability systems
Available for qualified candidates
