Job description

Are you obsessed with data, partner success, taking action, and changing the game? If you have a whole lot of hustle and a touch of nerd, come work with Pattern! We want you to use your skills to push one of the fastest-growing companies headquartered in the US to the top of the list. Pattern accelerates brands on global ecommerce marketplaces leveraging proprietary technology and AI. Utilizing more than 66 trillion data points, sophisticated machine learning and AI models, Pattern optimizes and automates all levers of ecommerce growth for global brands, including advertising, content management, logistics and fulfillment, pricing, forecasting and customer service. Hundreds of global brands depend on Pattern’s ecommerce acceleration platform every day to drive profitable revenue growth across 60+ global marketplaces—including Amazon, Walmart.com , Target.com , eBay, Tmall, TikTok Shop, JD, and Mercado Libre. To learn more, visit pattern.com or email press@pattern.com . Pattern has been named one of the fastest growing tech companies headquartered in North America by Deloitte and one of best-led companies by Inc. We place employee experience at the center of our business model and have been recognized as one of Newsweek’s Global Most Loved Workplaces®. We need a Senior Machine Learning Engineer to own evaluation systems and model-side quality improvements for Pattern's generative content platform, the system that produces AI-generated titles, bullets, A+ modules, and imagery across hundreds of thousands of listings. You will build reliable evaluation systems and improvements across non-deterministic systems and you will own the model-side work that acts on what those measurements find. This is a full-time role and will work a hybrid schedule based in Lehi, Utah. What is a day in the life of a Senior Machine Learning Engineer? Build and maintain the datasets, rubrics, and automated judges that evaluate the efficacy of changes to the content engine. Convert brand rejection reasons into structured, labeled training data that feeds the next round of model improvements. Find ways to quantify qualitative improvements to generated content. Decide and defend approval thresholds for generated content in partnership with data science and brand teams. Build quality gates that catch problematic outputs before they reach brand review, reducing rework cycles across the pipeline. What will I need to thrive in this role? Strong code and system design experience in any language or stack. 3+ years owning production software services end to end. Formal statistics or machine learning training, or a defensible equivalent depth built on the job. Experience engineering systems with non-deterministic outputs, where correctness has to be measured rather than assumed. Nice to have: Fine-tuning experience (LoRA/PEFT), hands-on LLM or generative media production work, evaluation-system ownership, multimodal evaluation, e-commerce domain knowledge, human-labeling operations, or A/B testing infrastructure. What is my potential for career growth? At Pattern, we prioritize internal mobility and professional development. This role sits at the intersection of software engineering and data science on one of Pattern's most visible AI systems, building deep expertise in evaluation design, fine-tuning, and production ML — experience that prepares you for senior IC or technical leadership tracks across Pattern's broader AI and generative content initiatives. What does success look like in the first 30, 60, 90 days? 30 Days: Complete onboarding, get up to speed on the generative content pipeline and existing evaluation datasets and rubrics, and make initial contributions to an existing regression suite. 60 Days: Own a defined slice of the evaluation system end to end (for example, judges and thresholds for a specific content type), and begin converting brand rejection reasons into labeled training data. 90 Days: Independently drive a fine-tuning or retrieval experiment from hypothesis to validated result, with at least one quality gate live in production catching issues before brand review. We want individuals who are: Game Changers- A game changer is someone who looks at problems with an open mind and shares new ideas with team members, regularly reassesses existing plans and attaches a realistic timeline to goals, makes profitable, productive, and innovative contributions, and actively pursues improvements to Pattern's processes and outcomes. Data Fanatics- A data fanatic is someone who recognizes problems and seeks to understand them through data, draws unbiased conclusions based on data that lead to actionable solutions, and continues to track the effects of the solutions using data. Partner Obsessed- An individual who is partner obsessed clearly explains the status of projects to partners and relies on constructive feedback, actively listens to partner's expectations, and delivers results that exceed them, prioritizes the needs of your partners, and takes the time to create a personable experience for those interacting with Pattern. Team of Doers- Someone who is a part of a team of doers uplifts team members and recognizes their specific contributions, takes initiative to help in any circumstance, actively contributes to supporting improvements, and holds themselves accountable to the team as well as to partners. What is the hiring process? Initial phone interview with Pattern's talent acquisition team Video technical interview Onsite interview with hiring manager and a panel of department leaders Professional reference checks Executive review Offer How can I stand out as an applicant? Discuss professional accomplishments with specific data to quantify examples Provide insights on how you can add value and be the best addition to the team Focus on mentioning how you would be partner obsessed at Pattern Share experience on any side projects related to data and analytics Why should I work at Pattern? Pattern offers big opportunities to make a difference in the ecommerce industry! We are a company full of talented people that evolves quickly and often. We set big goals, work tirelessly to achieve them, and we love our Pattern community. We also believe in having fun and balancing our lives, so we offer awesome benefits that include: - Unlimited PTO - Paid Holidays - Onsite Fitness Center - Company Paid Life Insurance - Casual Dress Code - Competitive Pay - Health, Vision, and Dental Insurance - 401(k) match. Pattern matches 100% of the first 3% in eligible compensation deferred and 50% of the next 2% in eligible compensation deferred. Pattern provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability, status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

Requirements

Must-haves

This is a full-time role and will work a hybrid schedule based in Lehi, Utah.
What is a day in the life of a Senior Machine Learning Engineer?
Build and maintain the datasets, rubrics, and automated judges that evaluate the efficacy of changes to the content engine.
Convert brand rejection reasons into structured, labeled training data that feeds the next round of model improvements.
Find ways to quantify qualitative improvements to generated content.
Decide and defend approval thresholds for generated content in partnership with data science and brand teams.
Build quality gates that catch problematic outputs before they reach brand review, reducing rework cycles across the pipeline.
What will I need to thrive in this role?
Strong code and system design experience in any language or stack.
3+ years owning production software services end to end.
Formal statistics or machine learning training, or a defensible equivalent depth built on the job.
Experience engineering systems with non-deterministic outputs, where correctness has to be measured rather than assumed.
What is my potential for career growth?
What does success look like in the first 30, 60, 90 days?
30 Days: Complete onboarding, get up to speed on the generative content pipeline and existing evaluation datasets and rubrics, and make initial contributions to an existing regression suite.
60 Days: Own a defined slice of the evaluation system end to end (for example, judges and thresholds for a specific content type), and begin converting brand rejection reasons into labeled training data.
90 Days: Independently drive a fine-tuning or retrieval experiment from hypothesis to validated result, with at least one quality gate live in production catching issues before brand review.
What is the hiring process?
Initial phone interview with Pattern's talent acquisition team
Video technical interview
Onsite interview with hiring manager and a panel of department leaders
Professional reference checks
Executive review
How can I stand out as an applicant?

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningllmml

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Professional Development