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Machine Learning Engineer (Recommender Systems)

• Posted 30+ days ago • Updated 10 hours ago

Full Time

On-site

Fitment

Dice Job Match Score™

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Job Details

Skills

Recruiting
Pricing
Scratch
Startups
Apache Velocity
Collaboration
Machine Learning (ML)
PyTorch
Training
Python
GraphQL
Node.js
Cloud Computing
Amazon Web Services
Google Cloud Platform
Google Cloud
Microsoft Azure
Real-time
Artificial Intelligence
Electronic Commerce

Summary

This Turn2 client is a fast-growing consumer tech company that is hiring a Machine Learning Engineer to build real-time recommendation and ranking systems for a widely used AI-driven shopping assistant. This is a high-impact, high-ownership role ideal for someone who thrives in fast-paced environments, ships quickly, and wants to shape how users experience search, personalization, and pricing across millions of products.

Why This Role Stands Out:

Immediate user impact: Your models power a real-world product used daily by a rapidly growing customer base.
Full ownership: Architect, build, and ship systems from scratch in a fast-moving, product-centric culture.
Startup velocity: Join a team of high-agency builders working to redefine how people shop.

What You'll Do:

Design large-scale systems to ingest and normalize data from 50+ external platforms, processing hundreds of millions of product listings.
Build and deploy end-to-end ML pipelines for ranking, recommendation, and personalization.
Collaborate with frontend and backend engineers to tightly integrate models into both web and app experiences.
Prototype backend services that support rapid experimentation and user-facing iteration.
Continuously optimize inference pipelines for latency, performance, and relevance.

What You Bring:

2+ years of hands-on experience building and deploying machine learning models in production.
Proven ability to ship features in fast-moving, consumer-facing environments.
Expertise in personalization, ranking models, embeddings, and real-time inference (PyTorch preferred).
Experience building data pipelines for large-scale training and predictions.
Proficient in Python and familiar with backend tech such as GraphQL, Node.js, gRPC, or Prisma.
Solid understanding of cloud platforms (AWS, Google Cloud Platform, or Azure) and deployment best practices.
A tinkering mindset-someone who builds side projects and thrives in early-stage product environments.

Bonus Points For:

Experience with real-time recommendation or search ranking systems at scale.
Exposure to fullstack development or a willingness to contribute across the stack.
Familiarity with applied AI in consumer tech or e-commerce settings.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91069959
Position Id: e8c9dc534d4e601120801724531127a0
Posted 30+ days ago

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