About this opportunity
Mai Placement lists this Machine Learning Engineer Forecasting Production Systems opportunity in newark, New Jersey. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Machine Learning Engineer – Forecasting & Production Systems
Newark, NJ
Salary: $120,000 – $180,000
Description / Position Overview
The business is operating without consistently reliable SKU-level forecasting, creating gaps in purchasing decisions, inventory planning, and revenue predictability.
This role exists to fix that.
You will own the development, deployment, and performance of forecasting systems that directly impact sales projections, demand planning, and purchasing decisions. This is not a research role. The expectation is clear: build models that work in production, improve accuracy over time, and drive measurable business outcomes.
Responsibilities
Forecasting Ownership
Own SKU-level forecasting models across sales, demand, and purchasing
Deliver forecasts that directly influence inventory and operational decisions
Continuously improve model accuracy through iteration, testing, and feedback
Production Systems
Deploy models into live environments used by operations and leadership
Own model lifecycle: monitoring, retraining, performance tracking
Ensure systems are stable, fast, and reliable under high-volume conditions
Data & Pipeline Ownership
Build and maintain data pipelines supporting real-time or near-term forecasts
Structure and clean large-scale transactional datasets
Optimize data flow for speed, accuracy, and scalability
Business Execution
Translate operational problems into predictive models
Work directly with purchasing and operations teams to refine outputs
Deliver usable forecasts — not theoretical models
Success Metrics (MANDATORY)
Forecast accuracy improvement (MAPE, RMSE, or similar) over time
Reduction in inventory overstock / stockouts
Adoption of forecasts by purchasing and operations teams
Model uptime and reliability in production environments
Speed of iteration and deployment cycles
Requirements
Proven experience deploying machine learning models into production
Strong Python and experience with Scikit-learn or similar tools
Strong statistical and predictive modeling foundation
Hands‑on experience with time series forecasting in real business settings
Experience working with large-scale / big data environments
Experience building data pipelines tied to ML systems
Ability to operate in fast‑paced, execution‑driven environments
Must-Haves
Built forecasting models used for real business decisions
Strong time series forecasting experience (sales, demand, SKU‑level preferred)
Experience working with large datasets and high‑volume systems
Ownership mindset — ability to deliver outcomes, not just models
Proven ability to execute quickly and adapt under changing conditions
Compensation
$150,000-$200,000 per year
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Worksite address
newark, NJ, 07175, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.