Machine Learning Expert

3 days ago


Alleppey, Kerala, India beBeeForecasting Full time US$ 1,00,000 - US$ 1,50,000
Unlocking Supply Chain Excellence with AI-Powered Demand Forecasting

We are transforming the supply chain management landscape by harnessing the power of artificial intelligence to drive precision demand forecasting and inventory replenishment.

The market potential for supply chain software is substantial and rapidly expanding. Over recent years, the global SCM software market has experienced a compound annual growth rate (CAGR) of approximately 9.4%.

About the Role

We seek an accomplished Senior Data Scientist / ML Engineer to design and deploy cutting-edge forecasting solutions at scale. This position combines hands-on machine learning expertise with robust software engineering practices to deliver scalable, reliable, and transparent forecasting capabilities.

Key Responsibilities:
  • Design, develop, and implement production-grade forecasting models
  • Create end-to-end machine learning pipelines for data ingestion, feature engineering, model training, and deployment
  • BUILD probabilistic models to quantify forecast uncertainty
  • Implement MLOps best practices including model versioning, monitoring, and CI/CD
  • Work with distributed training frameworks for scalable model development
  • Collaborate with cross-functional teams (engineering, product, strategy) to align solutions with business objectives

This role requires a hybrid work arrangement with 3 days of on-site work per week.

Facts About Our Company:

  • Employee Count: More than 500
  • Customer Count: Over 200
  • Revenue: $25M in Annual Recurring Revenue (ARR)
  • Profitable: Yes

We focus on disrupting the supply chain planning industry, providing technological advantages to small and medium-sized businesses (SMBs).

Requirements:

  • 3–6 years of experience in Data Science / ML Engineering
  • Strong proficiency in Python and core libraries such as pandas, numpy, scikit-learn
  • Hands-on experience with deep learning frameworks (preferably PyTorch)
  • Experience with distributed training and large-scale datasets
  • Proven ability to build scalable, production-grade ML pipelines
  • Familiarity with MLOps practices (CI/CD, monitoring, retraining pipelines)

Education:

  • MS or BS in CS or related from a top university
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