Machine Learning Engineer II, Ads - Response Prediction
Develop and deploy machine learning systems for Instacart’s advertising ecosystem, spanning data pipelines, model architectures, serving, experimentation, and optimization. The role requires a graduate degree and strong programming, analytical, and collaboration skills, with experience in large-scale ML systems preferred.
About the job
Responsibilities
- Design, develop, and deploy machine learning solutions, including data pipelines, model architectures, and serving integrations for ads-related challenges.
- Formulate ambiguous modeling problems and translate business observations into well-defined ML research directions with clear evaluation criteria.
- Collaborate with product managers, data scientists, and infrastructure engineers to create impactful ML applications.
- Improve operational efficiency by refining and advancing algorithms and models.
- Publish and present findings internally; contribute to design reviews, paper sharing, and experiment retrospectives.
Requirements
- Graduate degree (master's or PhD) in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field.
- Strong programming skills and fluency in data manipulation and machine learning tools.
- Strong analytical and problem-solving abilities.
- Effective communication and collaboration skills.
Nice-to-haves
- 1–2 years of industry experience applying machine learning to real-world problems with large datasets.
- Knowledge of sequential modeling, Transformer architecture, and foundation models.
- Familiarity with LLM integrations, agentic workflows, and productivity tooling.
- Experience building large-scale online recommendation systems.
Compensation and Benefits
- Base pay: CA$154,000–$162,500 CAD.
- Eligible for a new-hire equity grant and annual refresh grants.
- Benefits vary by employee location.
Skills
Machine Learning, SQL, Spark, pandas, Deep Learning, Sequential Modeling, Transformers, Foundation Models, LLMs, Recommendation Systems
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