Growth & Flexibility Through Pro5: Santosh’s Leap Forward as an ML Engineer in Logistics

How Santosh used Vertex AI to automate forecasting at a logistics leader, achieve remote work and global collaboration, and gain a 25% salary increase via Pro5.ai.

Summary

  • Role: Machine Learning Engineer
  • Industry: APAC logistics (enterprise scale)
  • Work style: Remote with global collaboration
  • Impact: Automated sales & demand forecasting with Google Vertex AI, improving accuracy and reducing manual work
  • Outcome: 25% salary increase, stronger cross‑border collaboration skills, and ownership of production‑grade ML pipelines
  • Why he recommends Pro5: Flexible, supportive experience that advances both career and work‑life balance

From Opportunity to Ownership—With Pro5.ai

For Santosh Pal, joining a Singapore-based logistics company as a Machine Learning Engineer through Pro5.ai wasn’t just a career move. It was a chance to build technology that improves real-world decisions while gaining global exposure.

Working for Pro5 has been incredibly rewarding, not just for my professional growth but also for the flexibility it allowed me,” Santosh shared.

Building a Production‑Grade Forecasting Engine on Vertex AI

Through Pro5.ai, Santosh took the lead in automating the company’s end‑to‑end sales and demand forecasting using Google Vertex AI:

  • Pipelines: Designed and built E2E ML pipelines—from data ingestion to model training to forecast generation.
  • Outcomes: Significantly improved forecast accuracy and eliminated repetitive manual work.
  • Delivery: The project was completed within a year and delivered measurable business impact.

What really excited me was seeing how automation could transform decision-making and efficiency at scale,” Santosh said. “I enjoyed the ownership I had in designing and deploying a production-grade pipeline that made a real difference to the company’s forecasting process.

Remote Work That Actually Works

Santosh thrives in a remote setup that supports deep focus and seamless teamwork across time zones.

I’ve been able to work from the comfort of my home while maintaining strong collaboration with global teams,” he said.
It’s the perfect balance of productivity and connection.

Compensation, Growth, and Global Skills

  • Compensation: A 25% increase recognized the value of his skills and the significance of his contribution.
  • Career Growth: Greater ownership across MLOps and cloud ML reinforced his technical trajectory.
  • Global Collaboration: Santosh says:
Interacting with colleagues and clients from around the globe has taught me new ways of approaching challenges and strengthened my teamwork,” he shared.

Why He Recommends Pro5

Santosh’s experience with Pro5 was both fulfilling and enabling—from the flexible work model to the chance to build systems that matter.

Overall, my journey with Pro5 has been deeply fulfilling, and I’m grateful for the opportunities they have provided me,” he said.

Based on this experience, Santosh recommends Pro5 to ML engineers who want remote flexibility, global-scale problems, and meaningful impact without the friction of a typical hiring process.

Results at a Glance

  • Title: Machine Learning Engineer
  • Domain: Logistics (APAC)
  • Key Work: Vertex AI‑powered demand & sales forecasting; automated E2E ML pipelines
  • Work Model: Remote with global collaboration
  • Business Impact: Higher forecast accuracy, reduced manual effort, faster decisions
  • Compensation: 25% increase vs. previous role

Ready to Find a Role That Fits?

Pro5.ai helps experienced professionals match with high‑impact roles, combining transparent communication, flexible work, and career‑advancing projects.

Find a role that feels right for you. Start your journey with Pro5.

Overview

What tech did Santosh use?
Google Vertex AI to orchestrate data ingestion, model training, and forecast generation in a production pipeline.

What changed for the business?
Improved forecasting accuracy and less manual work, enabling faster, better decisions.

How did Pro5 help?
Role matching that aligned with Santosh’s ML + MLOps strengths, a remote‑friendly setup, and a candidate‑first process.

What was the compensation outcome?
A 25% salary increase.