> Markdown version of [/jobs/ext/2209336-senior-machine-learning-engineer-digital-twin-platform](https://www.wearedevelopers.com/jobs/ext/2209336-senior-machine-learning-engineer-digital-twin-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer, Digital Twin Platform - **Company:** Instacart - **Location:** Canandaigua, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $240,000.0 - $253,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Computer Vision, Microsoft Azure, Cloud Computing, Inventory Management Software, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Software Deployment, Unstructured Data, Management of Software Versions, Digital Twin, Google Cloud, Pytorch, Scikit Learn, Information Technology, Machine Learning Operations, Data Pipelines - **Published:** August 24, 2026 - **Apply:** https://www.dice.com/job-detail/a4e1e734-2f75-4fab-99eb-2c748d7f540b ## About the Role * 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, Google Cloud Platform, 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 ## Description 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. ## Related Videos - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)