2 months ago
Responsibilities
- Lead high-impact ML projects across 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.
- Move model improvements such as teacher distillation, learned personas, and SFT rollouts from experimentation into production.
- Build scalable ML components, data pipelines, model-serving paths, golden datasets, trace replay systems, and benchmark infrastructure.
- Improve human-versus-agent alignment and behavioral fidelity through offline and online evaluation.
- Use behavioral and storefront data to improve buyer simulation, personalization, and merchant-facing recommendations.
- Diagnose model, data, and system failures and make practical tradeoffs across models, infrastructure, evaluation tools, and data systems.
- Collaborate with engineering, product, data, research, and partner teams while raising the team’s technical bar through execution, code quality, and mentorship.
Requirements
- Strong applied machine learning engineering experience delivering production systems through ambiguous technical problems.
- Hands-on experience with LLM, VLM, or agent systems, including SFT/post-training, distillation, evaluation, model iteration, or serving tradeoffs.
- End-to-end experience training, evaluating, testing, deploying, and operating ML products at meaningful scale.
- Strong experimentation and evaluation skills, including metric design and diagnosing 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 software engineering fundamentals, operational awareness, maintainability, execution speed, and communication with technical and non-technical audiences.
- Preferred experience with browser automation, AI agents, simulated user behavior, e-commerce, search, recommendations, personalization, buyer behavior modeling, sequence or behavior representation learning, recommender embeddings, HSTU-style architectures, vLLM/GPU serving, Spark/GCS/Hugging Face-style workflows, or translating research prototypes into reliable user-facing systems.
Benefits
- The role may require on-call work.
- The hiring process moves quickly and includes a technical interview loop with 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