ZipRecruiter

Log In

1

Assistant Recommender Systems Jobs (NOW HIRING)

3B Staffing LLC

MLOps Engineer

Indianapolis, IN · On-site

Hands-on experience working on recommender systems, drawing from ML techniques such as embedding ... Data Management and Collaboration: * Assist as needed with data labeling and management, ensuring ...

3B Staffing LLC

MLOps Engineer

Indianapolis, IN · On-site

Hands-on experience working on recommender systems, drawing from ML techniques such as embedding ... Data Management and Collaboration: * Assist as needed with data labeling and management, ensuring ...

Soteria Reinsurance Ltd.

$140 - $190/hr

Key assignments may include document processing and information extraction, schema mapping, enterprise assistants, recommender systems, and anomaly detection. The successful candidate must be ...

Soteria Reinsurance Ltd.

WI · On-site

$140 - $190/hr

Key assignments may include document processing and information extraction, schema mapping, enterprise assistants, recommender systems, and anomaly detection. The successful candidate must be ...

Namely

Senior Al Engineer

Mountain View, CA · On-site

$180 - $250/hr

... models, recommender systems, and other AI tools can make work more personal and efficient ... Learn about MLOps concepts such as model deployment, monitoring, and retraining. Assist in writing ...

next page

Showing results 1-20

All JobsRecommender Systems JobsAssistant Recommender Systems Jobs

Assistant Recommender Systems information

What cities are hiring for Assistant Recommender Systems jobs?

Cities with the most Assistant Recommender Systems job openings:

What are the most commonly searched types of Recommender Systems jobs?

The most popular types of Recommender Systems jobs are:

What states have the most Assistant Recommender Systems jobs?

States with the most job openings for Assistant Recommender Systems jobs include:

Assistant Recommender Systems jobs near you
Infographic showing various Assistant Recommender Systems job openings in the United States as of August 2026, with employment types broken down into 86% Full Time, 9% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Machine Learning Engineer (Recommender Systems)

Turn2Partners

Washington, DC • On-site

$129K - $155K/yr

Full-time

Re-posted 13 days ago

Job description

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, GCP, 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.

Apply