Top Machine Learning Engineer Jobs in Chicago
As a Machine Learning Engineer at Dropbox, you will design, build, evaluate, deploy, and iterate on large scale ML systems, collaborate with cross-functional teams, and impact millions of users with personalized experiences.
Machine Learning Engineer role at Cash App focusing on building machine learning models for fraud detection, customer support automation, and underwriting and credit evaluation. The role involves experimenting with state-of-the-art algorithms, using NLP for contextual inquiries, and integrating ML solutions for evaluating customer risks.
As a machine learning engineer, you will work on a large-scale machine learning system, contribute to recommender systems, and continuously improve solutions.
Work as a Machine Learning Engineer at ZS AI Practice, building transformative AI-enabled data products and solutions. Responsibilities include building model pipelines, scaling machine learning algorithms, enhancing ML engineering platforms, implementing ML Ops, writing production-ready code, collaborating with client teams, and researching latest technologies.
As a machine learning engineer at Tegus, you will build product features powered by machine learning on top of unique datasets. Your work will involve NLP and large language models. You will collaborate with product managers and engineers to prototype, build, and release features. A bachelor's degree in a quantitative discipline or relevant experience is required.
As an Applied Machine Learning engineer at Atlassian, you will work on the development and implementation of cutting-edge machine learning algorithms, training models, and collaborating with product, engineering, and analytics teams to integrate AI functionalities into Atlassian products and services. Responsibilities include designing system and model architectures, conducting rigorous experimentation, and applying AI/ML to improve product problems.
Seeking a Staff Machine Learning Engineer/Architect to lead the Machine Learning and Artificial Intelligence R&D strategy at Qualtrics. Responsibilities include designing AI architectures, frameworks, and algorithms, evaluating AI technologies, collaborating across teams, and deploying ML systems in production.
Senior AI/ML Engineer responsible for building AI & ML platforms and solutions for financial services and insurance. Develops data into usable information to create automated analytics solutions. Requires expertise in rapidly deploying AI & ML solutions in a DevOps environment, coding fluency in Python, R, or Java, experience with Kubeflow, Airflow, Docker, and Spark, and proficiency in data preprocessing, cleaning, and data visualization.
Featured Jobs
As a Senior Principle Machine Learning Engineer at Atlassian, you will integrate AI capabilities into Atlassian products, extract insights from data, develop robust models, collaborate with cross-functional teams, and promote AI within the organization.
Build, orchestrate, and monitor model pipelines, scale machine learning algorithms on massive data sets, implement ML Ops, write production-ready code, collaborate with client teams and global development team, research and evaluate latest technologies.
Experiment with state-of-the-art algorithms to improve knowledge retrieval and search efficiency, develop Natural Language Processing and Gen AI models to improve customer support effectiveness, collaborate with cross-functional teams, and continuously monitor and evaluate machine learning model performance.
Develop and implement machine learning models for fraud detection, analyze datasets, collaborate with cross-functional teams, monitor model performance, stay updated with the latest ML and fraud detection techniques, and present reports to stakeholders.
As a Principal Machine Learning Engineer at Atlassian, you will drive the development and implementation of cutting-edge machine learning algorithms, collaborate with various teams to integrate AI functionalities into products and services, and provide guidance to emerging ML engineers.
As a Principal Data Scientist, you will drive the experimentation practices and analyses, collaborating with business, engineering, and analytics teams, to enable trustworthy decisions at scale.
Senior Machine Learning Engineer focused on modeling and measurement within Square's GTM organization. Responsible for developing ML models and algorithms for strategic decision-making. Collaborate with various stakeholders to enhance Square's attribution system and drive growth.
Join Square as a Senior Machine Learning Engineer specializing in attribution space within the Measurement Machine Learning teams. Develop cutting-edge ML models and algorithms to provide insights for strategic investment decisions. Collaborate with various stakeholders to inform growth strategy with data-driven attribution solutions.
As a Senior Machine Learning Engineer at Grainger, you will play a central role in evolving and expanding machine learning infrastructures to enhance the customer journey. Your responsibilities include deploying and maintaining ML systems at scale, designing data pipelines, and collaborating with data scientists to deliver business impact through ML products.
As a Senior Machine Learning Engineer at Movable Ink, you will be responsible for advancing the core machine learning solution and infrastructure, building scalable models, and deploying them to production. You will work on recommender-system related challenges, collaborate with data engineers and platform engineers, and continuously improve the ML platform.
Seeking a Senior Machine Learning Engineer to apply machine learning to solve various problems, build infrastructure, and shape team development. Responsibilities include delivering AI-powered products, conducting data analysis, building ML models, and challenging conventional thinking. Must have 6+ years of experience in data science/machine learning, experience with AWS services, and proficiency in writing SQL queries.
Looking for a Senior Machine Learning Engineer to join our team in building and scaling our platform for access control and office automation. Responsibilities include building tools and data pipelines, optimizing algorithms, collaborating with cross-functional teams, conducting research, and generating patents or publications. Qualifications include a graduate degree in CS or a relevant field, 2+ years of industry experience, expert knowledge of C++ and/or Python, and experience in speech recognition.
Design and build batch and real-time inference services and tooling, facilitate modelers, develop prototypes, and influence team culture in a global financial crimes technology team using Machine Learning and Generative AI at Cash App.
Join the Data Science and Analytics Engineering team to build ML/NLP models and contribute to the automation of data processing. Require expertise in Machine Learning, deep learning, NLP, feature engineering, and optimization. Must have experience deploying ML models to production using AWS, GCP, or Azure.
Build product features powered by machine learning on top of unique, proprietary datasets. Focus on NLP and large language models. Collaborate with product managers and engineers to prototype, build, and release features. Write production python code and deploy microservices.
Design, build, and launch credit products and features for Cash App's Underwriting & Credit organization. Solve challenging technical problems at scale, collaborate with cross-functional teams, and mentor fellow engineers. Embrace changes in technology to promote future evolvability of tech stack.
The Senior Machine Learning Engineer (Modeling) - Underwriting and Credit role is part of Cash App's ML team and is deeply embedded within the Underwriting and Credit workstream. The engineer will work on building and integrating ML solutions for evaluating customer cash flow risk, including risk of default on credit obligations and risk of fraud & abuse of loans. The engineer will also be responsible for optimizing the automated decisioning pipeline using AI/ML techniques and collaborating cross-functionally with finance, product, and engineering teams.
All Filters
No Results
No Results