Sr. Machine Learning Engineer

Pattern builds a generative content platform that produces AI-generated titles, bullets, A+ modules, and imagery. In this full-time, hybrid role based in Lehi, UT, you will own evaluation systems and drive model-side quality improvements that help the content engine produce stronger outcomes with less rework.

What you’ll do

• Build and maintain the datasets, rubrics, and automated judges used to evaluate the effectiveness of changes to the content engine.
• Convert brand rejection reasons into structured, labeled training data that supports the next round of model improvements.
• Develop ways 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 that catch problematic outputs before they reach brand review, reducing pipeline rework cycles.

What you bring

• 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 is measured rather than assumed.
• Nice to have: Fine-tuning (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.

Benefits and support

• 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.

Growth at Pattern

Pattern emphasizes 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. You will build expertise in evaluation design, fine-tuning, and production ML, preparing you for senior individual contributor 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, and contribute 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.

How you’ll be evaluated

• Game changers bring open-minded problem solving, share new ideas, reassess plans with realistic timelines, and pursue improvements to processes and outcomes.
• Data fanatics use data to form unbiased conclusions and track results through data after solutions are implemented.
• Partner obsessed team members communicate status clearly, rely on constructive feedback, actively listen to expectations, and deliver results that exceed them.
• Team of doers supports teammates, takes initiative, and holds themselves accountable to both the team and partners.

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 to stand out

• Share accomplishments with specific data to quantify impact.
• Explain how you would add value and why you would be a strong fit for the team.
• Highlight how you would be partner obsessed at Pattern.
• Include experience from side projects related to data and analytics.