Sr. Machine Learning Engineer

Own evaluation systems and drive model-side quality improvements for a generative content platform producing AI-generated titles, bullets, A+ modules, and imagery.

• Build and maintain datasets, rubrics, and automated judges to evaluate changes to the content engine
• Convert brand rejection reasons into structured, labeled training data for the next model improvement cycle
• Identify approaches to quantify qualitative improvements in generated content
• Decide and defend approval thresholds for generated content in partnership with data science and brand teams
• Create quality gates to detect problematic outputs before they reach brand review, reducing rework across the pipeline

Requirements

• Strong code and system design experience in any programming language or stack
• 3+ years owning production software services end to end
• Formal statistics or machine learning training, or a defensible equivalent depth developed through hands-on work
• Experience engineering systems with non-deterministic outputs, where correctness is 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

Location and role details

• Location: Lehi, UT (hybrid)
• Experience: 3+ years
• Employment: Full-time

Benefits

• 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% and 50% of the next 2% (eligible compensation deferred)

Career growth

• Pattern prioritizes 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
• Work includes deep expertise in evaluation design, fine-tuning, and production ML
• Experience supports senior IC or technical leadership tracks across Pattern’s broader AI and generative content initiatives

First 30/60/90 days

• 30 Days: Complete onboarding, learn the generative content pipeline plus existing evaluation datasets and rubrics, contribute to an existing regression suite
• 60 Days: Own a defined slice of the evaluation system end to end (example: judges and thresholds for a specific content type), start 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 Pattern values

• Game Changers: Open-minded problem solving, new idea sharing, reassessing plans with realistic timelines, productive and innovative contributions, continuous process and outcome improvements
• Data Fanatics: Use data to understand problems, draw unbiased conclusions, deliver actionable solutions, track results with data
• Partner Obsessed: Clear status communication to partners, constructive feedback loops, active listening to expectations, delivering results that exceed expectations
• Team of Doers: Uplift teammates, recognize contributions, take initiative to help, support improvements, and maintain accountability to both team and partners

Hiring process

• Initial phone interview with Pattern talent acquisition team
• Video technical interview
• Onsite interview with hiring manager and a panel of department leaders
• Professional reference checks
• Executive review
• Offer

How to stand out

• Share professional accomplishments with specific, quantified examples
• Explain how you will add value and why you are a strong team fit
• Highlight how you would be partner obsessed at Pattern
• Include experience from side projects related to data and analytics