Senior Staff Applied ML Engineer - Consumer Agents

Saaspo; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Remote work in North America

Job summary

Shopify Inc. is seeking a Senior Staff Applied Machine Learning Engineer for Consumer Agents. This role focuses on distillation to own-GPU inference, agentic memory, and whole-page optimization acrossShopify’s consumer-facing AI agents.

You will own high-leverage problems end to end with minimal hand-holding. You will work at the intersection of LLM orchestration, model training, and cost/latency engineering, shipping weekly on a fast-moving surface with cross-team collaboration across Shopify’s

Qualifications

• Shipped LLM systems to production at real scale.
• Hands-on depth in model training and distillation in practice.
• Experience with serving and throughput-economics of inference.

Responsibilities

• Build and improve student models through supervised fine-tuning and knowledge distillation.
• Design and raise the bar for ML evaluation across the team with offline/online metrics.
• Develop agentic memory and personalization signals feeding predictive layers.
• Work on whole-page optimization for agent results surface.
• Build propensity and predictive models across agent surfaces.
• Move across distillation, memory, ranking, and evaluation as priorities shift.
• Apply rigorous experimentation on high-traffic surfaces with proper holdouts and A/B testing.
• Integrate with an LLM orchestration stack including tool calling and retrieval-augmented patterns.
• Be the technical reference point for the team on model and evaluation calls.

Skills

LLM systems production

model training and distillation

inference serving

evaluation methodology

autonomy in senior IC role

Tools

vLLM

structured output

Job description

Senior Staff Applied Machine Learning Engineer, Consumer Agents

Location: Remote - North America

About the role

The Consumer Agent team builds Shopify's consumer-facing agentic shopping experiences - the AI agents inside the Shop app and on merchant storefronts that help millions of buyers search, discover, and buy. As a Senior Staff Applied Machine Learning Engineer, you'll be the person we point at the hardest problems on the surface - distillation to own-GPU inference, agentic memory, whole-page optimization, propensity modeling, or the evaluation rigor that ties them together - and trust to drive it to a shipped, measured outcome. This is a senior individual-contributor seat with deep autonomy: you'll own ambiguous, high-leverage problems end to end, raise the bar for evaluation across the team, and ship weekly on a fast-moving consumer surface. You'll work at the intersection of LLM orchestration, model training and distillation, search and retrieval, and cost/latency engineering, partnering with frontier model labs and ML teams across Shopify.

Key Responsibilities

Build and improve student models through supervised fine-tuning and knowledge distillation, including the serving, generation-termination, and throughput-economics work that own-GPU inference demands.

Design and raise the bar for ML evaluation across the team - judge design, offline and online metrics, and the judgment to know when a number is real.

Develop agentic memory and personalization signals - buyer and user representations, profile generation - that feed predictive layers.

Work on whole-page optimization: page composition, ranking, and blending for the agent results surface.

Build propensity and predictive models for intent and purchase propensity across agent surfaces.

Move fluidly between distillation, memory, ranking, propensity, and evaluation as priorities shift, without lengthy re-tooling.

Apply rigorous experimentation on a high-traffic surface - proper holdouts, A/B rigor, and counterfactual or off-policy evaluation where online tests aren't enough.

Integrate cleanly with an LLM orchestration stack already in flight - tool calling, structured output, and retrieval-augmented patterns.

Become the technical reference point the team routes its hardest model and evaluation calls to.

Contribute to cross-team ML architecture conversations across Shopify's ML organization and external model-lab partnerships.

Ship weekly, absorbing ambiguity rather than adding coordination overhead.

Qualifications

You’ve shipped LLM systems to production at real scale - systems with real users, not research prototypes.

Hands-on depth in model training and distillation: supervised fine-tuning and knowledge distillation in practice.

Comfort with the serving and throughput-economics side of inference, not just the training run.

Rigorous evaluation methodology: judge design, offline and online metrics, and the judgment to distinguish a real result from an artifact.

You operate as a senior individual contributor with high autonomy - you take an ambiguous, hard problem and drive it quickly to a measured outcome without hand-holding.

Breadth over a single specialty: you can move across distillation, memory, whole-page optimization, propensity, and evaluation.

Strong communication and collaboration in a fast-paced, cross-functional environment.

Able to work with significant overlap with North America time zones.

Nice to have

E-commerce, marketplace, commerce-search, recsys, or ads background - with instincts for selection bias, position bias, and the gap between offline and online metrics.

Inference and serving internals: vLLM or similar engines, structured and constrained decoding, KV-cache and GPU throughput economics, and latency budgets.

Reinforcement learning experience - RLHF, RLAIF, or preference optimization.

Propensity, ranking, or classical applied ML at scale: gradient boosting, neural ranking, calibration, position-bias correction.

Counterfactual evaluation experience - inverse propensity scoring, doubly-robust estimators, off-policy evaluation.

Experience working alongside or with frontier AI products and agentic systems.

About the discipline

Engineering. It’s our DNA.

Engineering isn't a department at Shopify. It's our DNA. The engineers who thrive here care about the code, the system, and the merchants relying on both. They want hard problems and uncomfortable growth. They find solutions without waiting for permission. They ship weekly. They want commerce to work better for everyone. So does our founder, Tobi, who still codes and still shapes where this thing is going.

They're open source nerds. They pair program because two brains write better code than one. New tools, new models, new approaches. They experiment constantly. Most of what's standard here started as someone hacking on something.

They use AI like a keyboard, reflexively and everywhere, to clear the mundane and make room for thinking. And they work in the open. The fastest way to learn here is to watch someone better than you do the work. If that sounds like you, come build with us.

Infrastructure Engineers at Shopify build and maintain the systems that handle millions of requests per second and billions of dollars in transactions. At that scale, performance gains matter and weak assumptions surface quickly. Your systems power the experience for millions of entrepreneurs and buyers every minute of every day, including peak events like Black Friday.

Engineers at Shopify spend the majority of their time actually writing code to build and improve infrastructure. You'll solve problems that don't exist anywhere else, with challenges that push what's possible. If that lights you up, come build with us.

Growth and rewards

Mastery-matched compensation.

~Mastery

At Shopify, getting better at your craft and increasing your impact is how you grow. Twice a year, we assess both in our ~Mastery cycle, Shopify’s performance review. Achieving higher ~Mastery is a promotion, and when you earn a promotion your total rewards grow with it. Crafter and manager are equal paths, so you can pursue excellence in the craft you’re best at.

Total Rewards

With Flex Comp, your Rewards Wallet gives you agency over your compensation mix. Adjust your mix of cash, restricted share units, and stock options (including programs like Long-Term Equity)* to where it makes sense for you, and mix it up anytime as life and priorities change. Buying a house? Want more skin in the game? Just experimenting? It's your call.

* Flex Comp program offerings vary based on location, role, and employment type. Full details are set out in our Terms & Conditions and related plan documents.

Built for real life

Room for the rest of your life.

Flexible work, remote by design

A flexible vacation policy means most Shopifolk can take the vacation days they feel they need to recharge.

If a change of everyday scenery is more your jam, Destination 90 means you can work from (almost) anywhere in the world for 90 days of the year.

Your setup

Your battlestation is your home base. Request the desk, chair, and AV gear you need to get shit done.

• Our health and welfare benefits may include health, dental, vision, disability, and life insurance depending on your country.
• If you're in a country without a package, you'll receive a monthly allowance.
• We also offer mental health support for you and your dependents, including immediate and confidential services like counseling and coaching sessions.

Family support

• We offer fertility benefits globally, along with paid parental leave to welcome a new family member.

The Life Story is how we understand the themes of your career journey so far, human to human. What you've learned, and how you made a difference. Show us the trophies and the bruises: the problems you've solved, the challenges you encountered, the decisions you made, and the lessons you learned along the way.