Senior AI/ML Engineer

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5 năm kinh nghiệm
Hạn nộp hồ sơ: 30/12/2026 (Còn 55 ngày)
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Engineering has changed. We're changing with it. At [protected info], we build the software that helps eCommerce merchants win on search, discovery, and customer engagement. Building that well, in this market, means the engineering behind it can't stand still either.
AI has moved past being a coding aid, it's reshaping how software actually gets built, from spec to delivery, and we're moving with it rather than waiting for the dust to settle: agentic workflows, new tooling, new ideas about what a software factory even looks like. We build on and around Shopify, a platform that changes just as fast, so staying current isn't a nice to have here, it's the job.
That's why we're not hiring for where engineering was. We're hiring the next level of engineer, people who see this pace of change as the interesting part of the work, not something to survive until things settle down.
Your Impact
As a Senior AI/ML Engineer, you will design, build and run production AI/ML systems, from classic ML models to LLM and agent-based applications, that improve the user experience and business results. You will lead technical work on large AI systems, set a high bar for AI-native engineering practice, mentor engineers and work with stakeholders to define and deliver AI initiatives.
What You'll Do
Develop and maintain scalable ML pipelines on Databricks and AWS covering data ingestion, feature engineering, model training, evaluation and serving, with monitoring, drift detection and automated retraining.
Build systems that combine models, tools and data into cohesive, agentic workflows capable of executing multi-step tasks. This includes designing system behaviors such as planning, tool use, structured outputs and failure handling.
Identify and resolve performance bottlenecks in model training and inference through profiling, optimization, and architectural improvements, optimizing for latency and cost (e.g., TensorRT, quantization, batching).
Set up evaluation frameworks for LLM and ML systems, including offline evals, online A/B tests and quality guardrails, and ensure model fairness, bias mitigation and responsible AI practices.
Find and redesign engineering and business workflows using AI tools, and measure the impact.
Collaborate with cross-functional teams to translate product requirements into production-ready systems, and continuously improve system performance through iteration and evaluation.
Mentor engineers on ML practice and AI-assisted development.
What You'll Bring
5+ years of software engineering experience with a focus on machine learning systems, model development, or ML infrastructure
Proven track record of deploying AI/ML solutions at scale in production.
Experience in one or more specialized ML domains: search, recommendation systems, natural language processing (NLP), computer vision or generative AI.
Experience leading and owning end-to-end delivery of AI/ML projects, including technical design, cross-functional collaboration, and operational readiness.
Experience using Cursor, Copilot, Codex or similar AI coding assistants for development, debugging, testing and refactoring.
Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL and data exploration, and speeding up engineering workflows.
Has integrated AI tools to improve engineering efficiency and code quality, or to redesign workflows, with measurable impact such as time saved, defect reduction or throughput gains.
Keeps building AI skills, for example prompt and context engineering or agent orchestration, and stays current with new AI technologies.
Excellent communication and mentorship skills.
Good English communication skills (written and verbal)
Tech Stack
Languages: Python (primary)
Data & ML platform: Databricks (Spark, MLflow, Unity Catalog), AWS (SageMaker, S3, Lambda, ECS/EKS)
Vector search / RAG: Qdrant
Inference optimisation: TensorRT
Frameworks: PyTorch, Hugging Face; LLM APIs (Anthropic, OpenAI) and agent frameworks
Nice to have: LLM observability and eval tooling (e.g. Datadog LLM Observability), Docker/Kubernetes, CI/CD for ML
life at [protected info] eCommerce is crowded, noisy and increasingly complex. At [protected info], we're built for a different outcome: clarity you can act on.
We connect to the stack a merchant already uses. Our AI agents enrich their catalogue, learn from their reviews and customers, and put that intelligence to work inside the tools they already own - so their products get found, trusted and chosen by shoppers and AI, without replatforming.
We do this across our products: Clearer, Boost Commerce, [protected info] and Influence, used by thousands of merchants worldwide.
We're a global team with offices in Australia, the UK, Germany, Vietnam and the US, backed for the long term by PSG Equity and Silversmith Capital Partners.
We care about doing the work properly: listening first, building second and shipping quickly where it matters. Results matter more than rhetoric.
What guides us day to day:
Customers at the heart: we obsess over their needs so we can grow together
Purposeful progress: we don't settle - we take initiative and embrace bold thinking
Endless innovation: we refine, improve, and take meaningful action
Always open: we build trust through transparency and global collaboration
Clear Benefits
Everyone, everywhere
Your birthday off - a full paid day, just for you, every year
Give Back Day - a paid day each year to volunteer for a cause you care about
Bonusly peer recognition - real-time shout-outs tied to our values, with points that convert to real rewards
Clearer Together - employees who exemplifies our values wins a fully-funded 5-night trip to one of our global offices (Sydney, Berlin, Leicester, Irvine or Ho Chi Minh City)
Stopover - travelling near one of our offices? Once a year we'll fund a day with the local team
VN
100% Remote Culture: Work from anywhere in Vietnam that brings you happiness.
Performance-based Year-End Bonus: Recognizing and rewarding your individual contributions.
Wellness Allowance: Support for classes promoting physical and mental health.
Time Off: 20 days/year, in addition to Vietnam holidays.
MacBook Provided.
Collaborative Events: Offline meet-ups, monthly gatherings and year-end party.
Continuous Learning: Technical and general workshops, online resources.
Health and Wellness Benefits: Generali Health Care, annual check-up.
International Exposure: Enhance expertise and English communication skills.
a fair shot for everyone
We're committed to a fair and inclusive hiring experience. Hiring decisions at [protected info] are based on skills, experience and role requirements - nothing else. If you need any adjustments during the interview process, just tell us; it won't affect your application.

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