AI/ML Developer

Roles & Responsibilities AI / ML developer.

• Design and Implementation: Create machine learning models to solve specific problems.
• Algorithm Selection: Choose the right algorithms and techniques based on the problem.
• Model Training: Train models using available data.
• Performance Evaluation: Assess model performance using suitable metrics.
• Validation Testing: Test models for generalization and robustness using cross-validation.
• Model Integration: Integrate machine learning models into production systems or applications.
• API Implementation: Develop APIs and web services for model inference and prediction.
• Monitoring and Alerting: Set up systems to detect model degradation or data quality issues.
• Model Maintenance: Periodically update and retrain models to ensure effectiveness over time.
• Continuous Learning: Stay updated on the latest advancements and research in AI and ML.
• Experimentation: Explore new algorithms, frameworks, and tools to improve model performance.
• Participate in training sessions, workshops, and mentorship programs to enhance technical skills and knowledge.
• Assist in designing, developing, and implementing software applications, features, or modules under the guidance of senior developers or team leads.
• Write clean, well-documented, and efficient code using best practices and coding standards.
• Collaborate with team members to troubleshoot issues, debug code, and implement solutions.
• Write and execute test cases to ensure software functionality, reliability, and performance.
• Document technical specifications, design decisions, and implementation details.
• Collaborate with cross-functional teams including developers, designers, testers, and product managers.
• Communicate effectively with team members to understand requirements, share ideas, and coordinate tasks.
• Analyze requirements and propose creative solutions to technical challenges.