AI/ML Developer

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.