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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Infrastructure Engineer - **Company:** ESAI SOFTWARE INCORPORATED - **Location:** New York, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, C++ (Programming Language), Information Engineering, Data Files, Distributed Systems, Data Flow Control, Apache Hadoop, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Open Source Technology, Tensorflow, Data Processing, Google Cloud, Apache Spark, Deep Learning, Scikit Learn, Cassandra, Data Analytics, Apache Kafka, Machine Learning Operations, Functional Programming - **Published:** August 9, 2026 - **Apply:** https://www.wayup.com/i-j-startus-656482796972262/ ## About the Role + You have development experience with an object-oriented programming language such as C++ or Java and/or functional programming languages + You have previous industry experience with ML systems using frameworks such as Scikit-learn and Tensorflow + You have previously built APIs and libraries for Java, Scala or Python + You care about agile software processes, data-driven development, reliability, and responsible experimentation + You preferably have experience with data processing and storage frameworks like Google Cloud Dataflow, Hadoop, Scalding, Spark, Storm, Cassandra, Kafka, etc. + You preferably have machine learning publications or open source contributions to share with us + Skilled communicator and have a proven record of leading work across disciplines We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music. ## Description We are looking for a Senior Software Engineer to help us define and build the next generation of ML infrastructure at Spotify. Our mission is to enable every team at Spotify to iterate quickly on hypotheses and scale their experiments to data sets with hundreds of billions of data points. In this role you will work closely with many of the ML teams at Spotify across missions including ads targeting, personalization, music recommendations, pricing and more. Above all, your work will impact the way the world experiences music. WHAT YOU'LL DO + Build infrastructure to apply machine learning methods to massive data sets in production environments + Collaborate with cross functional agile teams of software engineers, data engineers, ML experts, and others in building new product features + Contribute to new and existing Spotify open source machine learning and data processing products (scio, featran, zoltar) + Leverage your experience to drive best practices in ML and data engineering + Gain a deep understanding of various models (collaborative filtering, NLP, deep learning) in order to understand their tradeoffs and bottlenecks + Design machine learning platforms and pipelines for training and running machine learning models on distributed systems + Determine the feasibility of projects through quick prototyping with respect to performance, quality, time and cost using Agile methodologies ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Introduction to TXT](https://www.wearedevelopers.com/videos/30-introduction-to-txt) - [Maximising Cassandra's Potential: Tips on Schema, Queries, Parallel Access, and Reactive Programming](https://www.wearedevelopers.com/videos/1167-maximising-cassandra-s-potential-tips-on-schema-queries-parallel-access-and-reactive-programming) - [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) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [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) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)