Principal Machine Learning Engineer

Job not on LinkedIn

🕒 August 6

🏈 Alabama, Alaska, +34 more states – Remote

🏈 Alabama – Remote 🐻 Alaska – Remote 🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🥔 Idaho – Remote 🌽 Illinois – Remote 🌪️ Kansas – Remote 🐎 Kentucky – Remote ⚜️ Louisiana – Remote 🎰 Nevada – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🌪️ Oklahoma – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote ❄️ Minnesota – Remote 🎸 Mississippi – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🗿 South Dakota – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ☕ Washington – Remote 🧀 Wisconsin – Remote 🦬 Wyoming – Remote

💵 $185k - $205k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 2%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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iFIT

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1977

🧘 Wellness

☁️ SaaS

🔧 Hardware

💰 $200M Private Equity Round - iFit on 2019-12

Wellness • SaaS • Hardware

iFIT is a connected fitness company that provides interactive workouts, personal training content, and a subscription-based fitness platform integrated with exercise equipment. iFIT publishes on-demand and live classes (Global Workouts, Progressive Series), offers mobile apps for iOS and Android, and supports equipment brands including NordicTrack and ProForm. The company operates a member center, customer support (live chat and texting), order tracking, and resources for memberships, troubleshooting, assembly and repair.

📋 Description

• Own the recommendation and search personalization strategy across product surfaces, defining the technical approach, prioritizing experiments, and driving decisions from offline evaluation to real-world user impact • Design and build end-to-end ML systems for ranking, retrieval, and personalization, including data pipelines, feature engineering, model training and evaluation, and production serving infrastructure • Drive relevance and ranking improvements through rigorous evaluation and experimentation • Partner with Product and Engineering to translate model behavior into product outcomes, collaborate on integration, and ensure reliable production performance • Collaborate with Data and Security to build safe, scalable personalization architecture addressing data access, privacy constraints, and operational requirements • Mentor engineers, contribute to hiring, and serve as the internal authority on ranking and personalization

🎯 Requirements

• Demonstrated experience building recommendation and/or search systems operating in production at scale • Strong ML engineering fundamentals, including ranking and retrieval, feature engineering, model training and evaluation, and practical deployment • Proven ability to connect model improvements to measurable user and product outcomes through structured experimentation • Strong software engineering skills, including reliable pipelines and services, maintainable code, and debugging complex distributed systems • Ability to communicate clearly with Product and Engineering partners, explain trade-offs, and align cross-functional teams • Authorized to work in the United States without sponsorship • Experience in health, fitness, or consumer-facing recommendation platforms (preferred)