Sobre este puesto de Machine Learning Engineer II, Ads - Response Prediction en Instacart
We're transforming the grocery industry
At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.
Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.
Instacart is a Flex First team
There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.
Overview
About the Role:
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart's ads systems. You will use machine learning to devise and refine solutions in crucial areas such as ads selection, ranking, bidding, and auction across all of Instacart’s consumer facing surfaces and Ads Ecosystems. You will actively contribute to initiatives, assisting in all stages of ML projects from the initial concept, through prototyping and experimentation, to final launch.
About the Team:
The Ads Response Prediction team owns systems, algorithms and ML models to ensure a relevant and engaging Ads experience to customers of all the platforms powered by Instacart. This includes search and exploration retrieval systems, Sequential Modeling and Generative Retrieval systems, LLM integrations, relevance models, pCTR models, bidding models and Foundation Models. The team optimizes for an efficient marketplace to ensure customers see ads that help them try new products/brands, advertisers boost their product sales for a good return on investment, and instacart generates the deserving revenue as well.
About the Job:
- Design, develop, and deploy machine learning solutions including data pipelines, model architectures and serving integrations to tackle practical challenges in the ads organization.
- Formulate and scope ambiguous modeling problems from first principles. Translate business observations (e.g., miss-calibration patterns, cold-start underperformance) into well-defined ML research directions with clear evaluation criteria.
- Collaborate closely with product managers, data scientists, and infrastructure engineers to deeply understand business needs and create impactful ML applications.
- Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.
- Publish and present findings internally. Contribute to the team’s culture of technical rigor through design reviews, paper sharing, and experiment retrospectives.
About You:
Minimum Qualifications:
- Have a graduate degree (masters or PhD) in machine learning, statistics, computer science, information retrieval, or a closely related quantitative field.
- Have strong programming skills and fluency in data manipulation (SQL, Spark, Pandas) and Machine Learning (classical ML and Deep Learning) tools.
- Have strong analytical skills and problem-solving ability.
- Are a strong communicator who can collaborate with diverse stakeholders across all levels.
Preferred Qualifications:
- Have 1-2 years of industry experience using machine learning to solve real-world problems with large datasets.
- Knowledge of sequential modeling, Transformer architecture and Foundation Model.
- Familiarity with LLM integrations, agentic workflow and productivity tooling.
- Experience in building large scale online recommendation systems.
#LI-Remote
Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Currently, we are only hiring in the following provinces: Ontario, Alberta, British Columbia, and Nova Scotia.
Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.
For Canadian based candidates, the base pay ranges for a successful candidate are listed below.
