Senior Machine Learning Engineer, Digital Twin Platform
Instacart
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Preparing for this interview
Interviews for learning roles keep coming back to Machine learning, Python, LLMs, PyTorch. Practise those questions before you sit with Instacart.
Questions you are likely to be asked
- Why do you want to join Instacart?
- What is your experience with Machine learning? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Senior Machine Learning Engineer, Digital Twin Platform at Instacart interview free →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
The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale.
We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In this role, you will develop machine learning models and deploy them into production systems, working in close collaboration with software engineers, computer vision engineers, product leads, and data scientists. If you're motivated by technically complex, high-impact problems and want to see your work shape how millions of people experience grocery shopping, this is the role for you.
You can read more about some of the work this team is doing here:
Introducing New Enterprise AI Solutions to Democratize AI for Grocers of All Sizes
Instacart Acquires Arpalus to Advance Real-Time Shelf Intelligence
About the Job
- Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale.
- Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact.
- Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation.
- Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline.
- Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business.
About You
Minimum Qualifications
- 5+ years of experience developing and deploying machine learning models in production environments.
- Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving.
- Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience.
Preferred Qualifications
- Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems.
- Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments.
- Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight.
- Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows and is consumed in those contexts.
- Experience collaborating closely with computer vision teams or incorporating vision-based signals into broader ML 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.
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 US based candidates, the base pay ranges for a successful candidate are listed below.
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Listed on greenhouse · posted 2026-08-20. ApplySarthi collects openings and links to application pages; the role is advertised by Instacart, not by us.