<div class="content-intro"><p><span style="font-family: arial, helvetica, sans-serif;">iFIT’s vision is to create the world's most holistic health and fitness platform, integrating all elements of health - physical fitness, mental health, nutrition and active recovery - into a seamless interactive experience. We develop proprietary software that learns and adjusts to the habits of each person as it delivers immersive content that guides them on their own individual fitness journey.</span></p></div><p> </p> <p class="font-claude-response-body break-words whitespace-normal"><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">We are currently seeking an ambitious pace-setter to join our team as a <strong>Principal Machine Learning Engineer remotely in the US.</strong></span></p> <p class="font-claude-response-body break-words whitespace-normal"><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">iFIT is looking for a technically exceptional and strategic Principal Machine Learning Engineer to own the recommendation and search personalization strategy across our product surfaces. In this role, you will design and build end-to-end ML systems, drive relevance and ranking improvements through rigorous experimentation, and partner with Product and Engineering to translate model behavior into meaningful product outcomes that keep our members engaged and progressing on their fitness journeys.</span></p> <p class="font-claude-response-body break-words whitespace-normal"><strong><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">COMPENSATION</span></strong><br><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">$185,000 - $205,000</span></p> <p class="font-claude-response-body break-words whitespace-normal"><strong><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">ROLE COMMITMENTS</span></strong></p> <ul class="[li_&]:mb-0 [li_&]:mt-1 [li_&]:gap-1 [&:not(:last-child)_ul]:pb-1 [&:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3 print:block print:space-y-1"> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Own and drive the recommendation and search personalization strategy across all product surfaces</li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Build end-to-end ML systems — data pipelines, feature engineering, model training, and production serving — that scale with the platform</li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Drive relevance improvements through rigorous experimentation, ensuring model gains translate to measurable user outcomes</li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Build a scalable, privacy-first ML architecture that addresses data access, compliance, and security requirements without slowing delivery</li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Raise ML fluency across R&D — mentor engineers, contribute to hiring, and serve as the internal authority on ranking and personalization</li> </ul> <p class="font-claude-response-body break-words whitespace-normal"><strong><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">ESSENTIAL DUTIES AND RESPONSIBILITIES</span></strong></p> <ul class="[li_&]:mb-0 [li_&]:mt-1 [li_&]:gap-1 [&:not(:last-child)_ul]:pb-1 [&:not(:last-child)_ol]:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3 print:block print:space-y-1"> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;"><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Own the recommendation and search personalization strategy across product surfaces — define the technical approach, prioritize experiments, and drive decisions from offline evaluation to real-world user impact.</span></li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;"><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">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.</span></li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;"><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Drive relevance and ranking improvements through rigorous evaluation and experimentation — design experiments, interpret results, and iterate quickly in response to new content, user behavior, and product surfaces.</span></li> <li class="font-claude-response-body whitespace-normal break-words pl-2" style="font-size: 12pt; font-family: arial, helvetica, sans-serif;"><span style="font-size: 12pt; font-family: arial, helvetica, sans-serif;">Partner with Product and Engineering to translate model behavior into product outcomes, collaborate on integration, and ensure systems perform reliably in production.</s