Machine Learning Engineer

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 leading global technology and logistics organization operates a large-scale delivery platform that connects merchants, consumers, and delivery professionals. Its Drive business enables deliveries placed through merchants’ own channels, including websites, mobile applications, and phone orders, by leveraging an extensive logistics network.

Key Responsibilities

• Build next-generation machine learning models for delivery ETA, pickup ETA, merchant preparation-time estimation, and order release prediction.
• Develop deep learning models using large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.
• Apply reinforcement learning and optimization techniques to improve logistics decision-making, assignment strategies, and marketplace efficiency.
• Build AI-native product experiences using large language models (LLMs) and vision-language models (VLMs).
• Transform pickup photos, item verification flows, receipts, and drop-off images into structured quality signals to verify orders, prevent delivery defects, and improve issue resolution.
• Design and conduct rigorous online experiments to evaluate and improve machine learning systems.
• Implement production monitoring and continuous model iteration to maintain performance and reliability.
• Partner closely with software engineers, product managers, data scientists, and platform teams to bring machine learning capabilities into production at scale.
• Develop and maintain machine learning systems that deliver measurable improvements for merchants, consumers, and delivery professionals.
• Solve large-scale estimation, ranking, prediction, optimization, and decision-making problems using advanced machine learning techniques.

Ideal Candidate Profile

• Enjoys solving large-scale machine learning problems with direct business and customer impact.
• Demonstrates strong ownership and takes machine learning models from research and experimentation through production.
• Comfortable working in ambiguous environments where experimentation and iteration inform product decisions.
• Values both model quality and production reliability.
• Excited to work across diverse machine learning techniques, including neural networks, optimization, reinforcement learning, and multimodal AI.
• Collaborates effectively with engineering, product, and data science teams.

Required Qualifications

• 5+ years of industry experience building and shipping production machine learning systems with measurable business impact.
• Bachelor’s, Master’s, or PhD degree.
• Strong experience developing production machine learning models using modern deep learning frameworks such as PyTorch.
• Experience with distributed data processing technologies such as Spark and Airflow.
• Experience building, deploying, monitoring, and maintaining production machine learning systems end-to-end.
• Strong software engineering skills in Python.
• Experience working with modern machine learning infrastructure and tooling.
• Deep expertise in at least one of the following areas:
  • Deep Learning
  • Reinforcement Learning
  • Optimization / Operations Research
  • Large Language Models (LLMs)
  • Vision-Language Models (VLMs)
• Experience applying machine learning to estimation, ranking, prediction, optimization, or decision-making problems at production scale.
• Proficiency using AI-assisted development tools such as Claude Code, Codex, or Cursor throughout the software development lifecycle.
• Located in or planning to relocate to San Francisco, CA; Sunnyvale, CA; or Seattle, WA.

Preferred Qualifications

• Hands-on experience with LLMs or VLMs.
• Experience working in logistics, marketplaces, delivery platforms, or similar large-scale operational environments.
• Experience developing AI-powered solutions involving images, receipts, delivery photos, or other multimodal data.
• Strong understanding of large-scale marketplace and behavioral data.
• Experience improving machine learning systems through experimentation, monitoring, and continuous iteration.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

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.
3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.