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Assistant Recommender Systems Jobs (NOW HIRING)

NavitasPartners

Systems Analyst - WIR #3

Milwaukee, WI · On-site

Recommend system improvements and enhancements * Collaborate with developers, testers, and stakeholders * Support system implementations, upgrades, and integrations * Assist with testing, debugging ...

NavitasPartners

Systems Analyst - WIR #3

Milwaukee, WI · On-site

Recommend system improvements and enhancements * Collaborate with developers, testers, and stakeholders * Support system implementations, upgrades, and integrations * Assist with testing, debugging ...

NavitasPartners

Systems Analyst - WIR #3

Wauwatosa, WI · On-site

Recommend system improvements and enhancements * Collaborate with developers, testers, and stakeholders * Support system implementations, upgrades, and integrations * Assist with testing, debugging ...

NavitasPartners

Systems Analyst - WIR #3

Wauwatosa, WI · On-site

Recommend system improvements and enhancements * Collaborate with developers, testers, and stakeholders * Support system implementations, upgrades, and integrations * Assist with testing, debugging ...

NavitasPartners

Systems Analyst - WIR #3

Greenfield, WI · On-site

Recommend system improvements and enhancements * Collaborate with developers, testers, and stakeholders * Support system implementations, upgrades, and integrations * Assist with testing, debugging ...

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Assistant Recommender Systems information

What are the most commonly searched types of Recommender Systems jobs? The most popular types of Recommender Systems jobs are:
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Machine Learning Engineer (Recommender Systems)

Machine Learning Engineer (Recommender Systems)

Turn2Partners

Washington, DC • On-site

$129K - $155K/yr

Full-time

Posted 17 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