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Senior Machine Learning Engineer

SpringCube

Full time - Senior Engineer

Logistics & Transportation

United States, Boston - Massachusetts

Published 2 weeks ago

Salary: USD8,000 - USD10,000

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview
A rapidly growing logistics technology company is building modern, end-to-end infrastructure to optimize ecommerce shipping, delivery, and returns. The organization leverages next-generation technology and a vertically integrated supply chain to give brands and customers unprecedented control over their deliveries. Their clients include leading consumer brands, and they focus on creating seamless post-purchase experiences, deepening customer loyalty, and driving lifetime value. The company emphasizes a merit-based culture and rewards high-performing, impact-driven team members with equity and career growth opportunities.

Summary
The Senior Machine Learning Engineer will work closely with data scientists and software engineers to design, build, and deploy machine learning models that improve the logistics network and user experiences. This role focuses on MLOps infrastructure, model deployment, monitoring, and performance optimization, bridging platform capabilities with advanced modeling initiatives.

Responsibilities

  • Build reliable, efficient, and scalable infrastructure for AI/ML capabilities
  • Create robust data pipelines to feed analyses and models
  • Enable forecasting, network orchestration, and live pricing systems
  • Ensure data quality and integrity through best practices in data integration
  • Develop feature stores, model orchestration tools, experimentation tooling, and model performance monitoring
  • Establish standards and templates for model development and deployment across Data Science teams
  • Collaborate closely with data scientists to maintain production models and address production incidents
  • Apply ML/MLOps knowledge to suggest improvements in tools, patterns, and approaches

Qualifications

  • Bachelor’s Degree plus at least 3 years of experience in machine learning engineering, or Master’s Degree plus at least 2 years of experience
  • Experience developing and optimizing MLOps pipelines for speed, reliability, and observability
  • Proficiency in Python and SQL
  • Hands-on experience with open-source tools for large-scale ML (e.g., Ray, Flink, Feast)
  • Experience with Data Warehouses (e.g., Redshift, Databricks, Snowflake)
  • Familiarity with cloud-based data engineering and data science tools (AWS preferred)
  • Experience building ML systems in startups is a plus
  • Experience with DS/ML in logistics or supply chain is a plus
  • Strong collaboration, problem-solving, and communication skills

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
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