Remote ML Engineer: Ranking & Retrieval

Parallel Partners, Inc.; San Francisco (CA); Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical insurance

Dental

Vision

Savings plan

PTO

Job summary

Parallel Partners, Inc. is seeking a Machine Learning (ML) Engineer to build and improve ML systems powering AI-driven applications.

You will work on classification, retrieval, ranking, personalization and evaluation, taking ownership from model development to production deployment in a fully remote environment. The role requires ML and AI experience, strong foundations in modern neural architectures, and hands-on deployment of models.

Qualifications

• Machine Learning experience is required.
• Artificial Intelligence experience is required.
• Strong foundations in ML and modern neural architectures.
• Hands-on experience building and deploying ML models in production.
• Experience in classification, ranking, retrieval, recommendation systems or personalization.
• Understanding of model evaluation, experimentation and performance metrics.
• Comfortable writing production-quality code and working with real-world datasets.
• Able to balance model quality, latency, cost and reliability.
• Strong ownership and problem-solving skills.
• Tech Stack: Embeddings, vector search and ranking models, Python and PyTorch/JAX.

Responsibilities

• Build and improve ML models for classification, ranking, retrieval and personalization.
• Develop efficient classifiers and optimize model accuracy, latency and cost.
• Improve search relevance and context retrieval using embeddings, hybrid search and reranking.
• Build personalization models that learn from user behavior while respecting privacy.
• Develop evaluation pipelines, labeled datasets and metrics to measure model quality.
• Fine-tune and adapt existing models when data allows.
• Build and maintain ML training, inference and deployment pipelines.
• Debug production issues, monitor model performance and ship improvements.
• Ensure ML models meet accuracy, relevance, latency and reliability targets.
• Collaborate with engineering and product teams to deliver ML-powered features.

Skills

ML experience

AI experience

Neural architectures

Production code

Classification

Ranking

Retrieval

Personalization

Model evaluation

Datasets

Ownership

Python

PyTorch/JAX

Tools

Embeddings

Vector search

Ranking models

Production ML systems

Inference pipelines

Python

PyTorch/JAX

Job description

Parallel Partners, Inc. is seeking a Machine Learning (ML) Engineer to build and improve ML systems powering AI-driven applications.

You will work on classification, retrieval, ranking, personalization and evaluation, taking ownership from model development to production deployment in a fully remote environment. The role requires ML and AI experience, strong foundations in modern neural architectures, and hands-on deployment of models.