- Location
- Americas (Remote)
- Compensation
- Not stated in this snapshot
- Employment
- Not stated
- Experience level
- STAFF (10+ years exp)
- Specialization
- Machine Learning Engineer, Machine Learning, Shopify
- Source
- Shopify
Role Overview
Discipline / Category: Applied ML (Applied ML Engineering)
Shopify is hiring for a Staff Applied Machine Learning Engineer, SimGym. Shopify is a digital by default company where employees work remotely across the Americas.
About The Role
Shopify is building SimGym, an AI-powered store testing system that simulates buyer behavior using browser automation and LLM/VLM agents. SimGym helps merchants understand how real shoppers might experience their storefronts, then turns those simulations into trustworthy, merchant-facing theme insights and recommendations.
We are looking for a Staff Applied Machine Learning Engineer to set and drive the ML technical direction for SimGym. This is a senior technical leadership role for someone who can move between strategy and code: defining the roadmap, designing production ML systems, de-risking ambiguous research, mentoring senior engineers, and shipping model improvements that create real merchant impact.
You will work across multimodal browsing agents, teacher-model distillation, learned buyer personas, SFT/post-training, evaluation systems, behavioral data pipelines, and production rollout infrastructure. The goal is not just to improve benchmarks, but to build AI agents that behave more like real buyers and produce recommendations merchants can trust.
Responsibilities
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Own the ML technical direction across SimGym's agent, persona, evaluation, and data flywheel workstreams.
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Develop, fine-tune, evaluate, and deploy LLM/VLM-based systems for browser automation, buyer simulation, and storefront analysis.
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Lead major model initiatives from research prototype to production readiness, such as VLM teacher distillation, learned buyer personas, or SFT model rollout.
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Design scalable ML architectures, data pipelines, and model-serving systems that support experimentation, evaluation, and production deployment.
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Improve human-vs-agent alignment and behavioral fidelity through rigorous offline and online evaluation.
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Build and stabilize golden datasets, trace replay systems, screenshot/A11y-tree evaluation flows, and reliable benchmark infrastructure.
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Use Shopify-scale behavioral and storefront data to improve buyer simulation, personalization, and merchant-facing recommendations.
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Make clear build/buy tradeoffs across models, infrastructure, evaluation tooling, and data systems.
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Communicate technical direction and tradeoffs clearly with engineering, product, data, research, and partner teams.
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Raise the technical bar for the team through hands-on implementation, design review, mentorship, and pragmatic execution.
What You'll Need
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Staff-level applied ML leadership experience, with a track record of setting strategy, writing code and designs, unblocking teams, and delivering production systems through ambiguity.
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Strong hands-on experience with LLM, VLM, or agent systems, including SFT/post-training, distillation, evaluation, model iteration, and serving tradeoffs.
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End-to-end experience training, evaluating, testing, deploying, and operating ML products at scale.
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Strong instincts for experimentation and evaluation, including designing meaningful metrics, diagnosing alignment failures, and avoiding misleading benchmark wins.
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Experience building production ML data pipelines and working with large-scale behavioral, event, or product data.
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Proficiency with Python, shell scripting, batch and streaming data pipelines, orchestration tools, vector databases, BigQuery/BigTable or equivalent systems.
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Experience with parallel or distributed ML environments, including GPU optimization, model serving, or large-scale training/inference workflows.
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Excellent communication with technical and non-technical audiences.
Preferred Qualifications
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Experience with browser automation, AI agents, or simulated user behavior.
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Background in e-commerce, search, recommendations, personalization, or buyer behavior modeling.
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Experience with sequence or behavior representation learning, recommender embeddings, HSTU-style architectures, vLLM/GPU serving, Spark/GCS/Hugging Face-style data workflows.
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Prior experience translating research prototypes into reliable, production user-facing systems.
Why This Role
This is a high-leverage role at the center of Shopify's applied AI work for merchants. You will help shape SimGym's ML architecture and operating model while working on frontier LLM/VLM agents, learned buyer personas, evaluation science, and production systems with direct merchant impact.
This role may require on-call work. Shopify's hiring process moves quickly, and candidates should be prepared for a technical interview loop that includes pair programming using their own IDE.
Requirements & Qualifications
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Demonstrated background and expertise relevant to Staff Applied Machine Learning Engineer, SimGym at Shopify.
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Strong communication and ability to work in a remote, fast-paced environment.
Total Rewards & Flex Comp
Shopify offers a flexible compensation system (Flex Comp) that allows employees to choose their own balance between cash (base salary) and equity (RSUs and stock options). Work is digital by default with remote flexibility across the Americas.