[Hiring] Machine Learning Engineer @Map Ssg

Role Description

We’re recruiting for an early-stage consumer AI company building a mobile app that helps people stay on top of messages, surface what needs their attention, and coordinate plans.

You’ll join a small ML team and own the models that decide what the app retrieves, ranks, and surfaces for each user. You’ll take models from training and evaluation through deployment, then use real-world feedback to improve relevance, latency, and reliability.

What you’ll do

• Build and ship models for ranking, retrieval, classification, and personalization.
• Improve search relevance and context retrieval using embeddings, hybrid search, and reranking.
• Use behavioral signals to personalize results while respecting user privacy.
• Build labeled datasets and evaluation pipelines to measure quality and catch regressions before release.
• Own training, inference, and deployment. Monitor live performance, debug production issues, and improve accuracy, latency, and cost.

Qualifications

• 2+ years of industry experience as a machine learning engineer, applied scientist, or in a similar hands-on role.
• A ranking, retrieval, or recommendation model you personally built and shipped to production. Consumer search, feeds, discovery, and marketplace recommendations are especially relevant.
• Experience with model serving and monitoring, and the ability to explain what you owned, how you measured quality, and what changed after launch.
• Strong Python skills and experience with a deep learning framework. The team uses PyTorch and JAX.
• Experience with behavioral personalization, classification, or offline evaluation and online A/B testing is a plus.

Requirements

• Fully remote work environment.
• Preference for candidates in the U.S. and Canada; candidates in Europe are also considered.
• Must already have work authorization in their country of employment. Visa sponsorship is unavailable.

Benefits

• U.S. base salary of $185K–$280K, plus equity and a discretionary performance bonus.
• Compensation outside the U.S. is benchmarked locally.