Sr. Machine Learning Engineer

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.