2 months ago
Responsibilities
- Own the ML technical direction for SimGym’s agent, persona, evaluation, and data-flywheel workstreams.
- Develop, fine-tune, evaluate, and deploy LLM/VLM systems for browser automation, buyer simulation, and storefront analysis.
- Lead model initiatives from research prototypes through production readiness, including distillation and SFT model rollouts.
- Design scalable ML architectures, data pipelines, and model-serving systems for experimentation and production deployment.
- Improve human-agent alignment and behavioral fidelity through offline and online evaluation.
- Build golden datasets, trace replay systems, screenshot/accessibility-tree evaluation flows, and benchmark infrastructure.
- Use large-scale behavioral and storefront data to improve simulation, personalization, and merchant recommendations.
- Mentor engineers, lead design reviews, communicate technical tradeoffs, and raise the team’s technical bar.
Requirements
- Staff-level applied ML leadership experience setting strategy, writing code and designs, unblocking teams, and delivering production systems through ambiguity.
- Hands-on experience with LLM, VLM, or agent systems, including SFT/post-training, distillation, evaluation, model iteration, and serving tradeoffs.
- End-to-end experience training, evaluating, testing, deploying, and operating ML products at scale.
- Strong experimentation and evaluation skills, including metric design and diagnosis of alignment failures.
- Experience building production ML data pipelines and working with large-scale behavioral, event, or product data.
- Proficiency with Python, shell scripting, batch and streaming data pipelines, orchestration tools, vector databases, and BigQuery/BigTable or equivalent systems.
- Experience with parallel or distributed ML environments, GPU optimization, model serving, or large-scale training and inference workflows.
- Strong communication with technical and non-technical audiences.
- Preferred experience with browser automation, AI agents, simulated user behavior, e-commerce, search, recommendations, personalization, or buyer behavior modeling.
- Preferred experience with sequence or behavior representation learning, recommender embeddings, HSTU-style architectures, vLLM/GPU serving, Spark/GCS/Hugging Face-style workflows, and translating research prototypes into reliable production systems.
Benefits
- The role may require on-call work.
- Shopify’s hiring process moves quickly.
- The technical interview loop includes pair programming using the candidate’s own IDE.
Tech Stack
Categories
About Shopify
Shopify is a leading global commerce company, providing trusted tools to start, grow, market, and manage a retail business of any size. Shopify makes commerce better for everyone with a platform and services that are engineered for reliability, while delivering a better shopping experience for consumers everywhere. Shopify powers millions of businesses in more than 175 countries and is trusted by brands such as Allbirds, Gymshark, PepsiCo, Staples, and many more. Find all our jobs here: www.shopify.com/careers