Soham Choudhury

A dedicated and results-driven Training Specialist with hands-on experience in designing, delivering, and optimizing training programs related to Machine Learning (ML) operations. Specialized in supporting Pre-Pod programs like Sparrow, Cardinal, and Stow to Fabric Pod, ensuring workforce readiness, process efficiency, and alignment with ML data operations.

Key Responsibilities:

1. Training Program Development:

• Design and implement training modules for ML data operations with a focus on Sparrow, Cardinal, and Stow to Fabric Pod.
• Develop instructional materials, SOPs, and hands-on training exercises tailored to program needs.

2. Facilitation & Delivery:

• Conduct in-person and virtual training sessions for new hires and existing employees.
• Use data-driven insights to customize training approaches for better knowledge retention.

3. Process Optimization & Support:

• Collaborate with ML engineers and operations teams to refine training workflows.
• Provide feedback on process improvements to enhance efficiency and accuracy.

4. Performance Monitoring & Reporting:

• Assess trainee performance through evaluations, quizzes, and on-the-job assessments.
• Track and report training effectiveness using key metrics and dashboards.

5. Stakeholder Collaboration:

• Work closely with cross-functional teams, including ML engineers, operations managers, and program leads, to ensure alignment with business goals.
• Act as a liaison between leadership and frontline employees to bridge training gaps.

6. Continuous Improvement & Innovation:

• Stay updated on AI/ML advancements and automation trends to refine training strategies.
• Introduce innovative learning methods such as simulations, gamification, and AI-assisted training tools.

Key Skills & Competencies:

• Strong understanding of ML data operations and automation workflows
• Hands-on experience with Pre-Pod programs (Sparrow, Cardinal, Stow to Fabric Pod)
• Instructional design & training delivery expertise
• Process optimization & stakeholder collaboration
• Performance analysis & reporting using data-driven insights
• Excellent communication & leadership skills

• Team Leadership & Mentorship: Led a team of 10 in ML data operations, ensuring high performance, skill development, and process adherence.
• Process Optimization: Identified and implemented efficiency improvements in ML data labeling, annotation, and validation workflows.
• Cross-Functional Collaboration: Partnered with engineers, data scientists, and program managers to align ML operations with business objectives.
• Quality Control & Performance Metrics: Monitored data accuracy, resolved anomalies, and ensured compliance with AI/ML model training standards.
• Training & Upskilling: Designed and conducted training sessions to enhance team proficiency in ML tools, automation, and data handling best practices.
• Project & Stakeholder Management: Managed project timelines, resource allocation, and stakeholder communication for seamless execution of ML initiatives.

• Data Annotation & Labeling: Used Nike annotation tool to accurately label and annotate large datasets for machine learning model training.
• Quality Assurance: Reviewed and corrected labeled data to maintain high accuracy, ensuring compliance with ML data standards.
• Tool Utilization: Operated Nike efficiently to enhance data processing speed and precision.
• Collaboration: Partnered with data scientists and engineers to align data labeling with project requirements.
• Documentation & Reporting: Tracked annotation progress and quality metrics, providing reports for process improvement.
• Process Optimization: Suggested enhancements for Nike tool workflows to improve annotation efficiency and reduce errors.

• Worked as an Academic Content Writer on distinctive topics related to STEM to help students of foreign universities in their academic projects