Top Machine Learning Engineer Jobs
The Machine Learning Engineer will lead the development and deployment of machine learning models to assess business risks using large datasets. Responsibilities include project ownership, collaborating with product management, and working within two-week sprints.
As a Machine Learning Engineer, you'll analyze complex datasets, develop models and algorithms, manage ML Ops, and enhance customer products. You'll communicate insights to senior management, supervise data analysis, and promote effective cross-functional collaboration within the team.
As a Machine Learning Engineer at Kalepa, you will lead the development, deployment, and scaling of machine learning models to analyze and understand business risks using diverse data sources. The role involves collaborating with Product Management and Software Engineers to drive project direction.
The Machine Learning Engineer will frame, develop, and deploy machine learning models to analyze risk for various businesses. They will work with both structured and unstructured data to derive insights, collaborating closely with product management and software engineering teams during two-week sprints, maintaining project ownership.
Snap Inc is looking for a Machine Learning Engineer to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building scalable products. Strong understanding of machine learning algorithms and frameworks like TensorFlow is required.
Snap Inc is looking for a Machine Learning Engineer to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building scalable products with exceptional code quality. Strong collaboration, mentorship skills and machine learning expertise are required.
Snap Inc is looking for a Staff Machine Learning Engineer to create models that drive value for users, advertisers, and the company. The role involves evaluating technical tradeoffs, performing code reviews, building scalable products, and iterating quickly without compromising quality.
As a Principal Machine Learning Engineer at Snap Inc, you will design and scale machine learning components and services, build a training framework for large-scale model training, optimize training performance using GPUs, develop an AutoML platform, and collaborate across teams to deliver innovative solutions, while advocating for best practices in scalability and operational excellence.
Featured Jobs
Lead the technical direction of the Ad Ranking team at Snap, focusing on advancing ML capabilities for ad optimization. Design and scale machine learning models, collaborate with cross-functional teams, and stay current with ML technologies to solve complex advertising-related problems.
As a Principal Machine Learning Engineer, you will drive the technical roadmap of Snap's Ad Marketplace and Pacing teams, design and scale machine learning models for optimal ad delivery, and collaborate with cross-functional teams. You will stay updated on the latest in machine learning to solve complex problems, advocate for best practices, and provide technical direction to influence the ML community.
As a Senior Machine Learning Engineer on the Personalization team, you will leverage machine learning to enhance customer experiences and drive growth for Cash App. You will work closely with product and marketing teams to develop and deploy machine learning models tailored to customer interactions, utilizing a rich data set for personalized recommendations.
As a Machine Learning Engineer, you will lead the framing, development, and deployment of machine learning models at scale to assess the risk of various business classes, turning large amounts of structured and unstructured data into actionable insights. You will work collaboratively in a two-week sprint cycle with product and software engineering teams.
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, scale machine learning algorithms, implement ML Ops, write production-ready code, and collaborate with global teams to deliver projects. You'll also research and evaluate new technologies and maintain high-quality deliverables.
As a Machine Learning Engineer at JPMorgan Chase, you will build and train production-grade ML models, develop end-to-end ML pipelines, and collaborate with teams to enhance data modeling experiments. Your role will include applying machine learning algorithms, producing high-quality production code, and conducting feature engineering.
As a Machine Learning Engineer III, you will design, develop, and implement ML and optimization models for various applications, collaborate with multi-functional teams, deploy science models using cloud resources, and mentor the data science team in best practices for model development.
The Staff Machine Learning Engineer will enhance batch inference services and tooling for financial crime detection, work on infrastructure for model development, and lead AI/ML initiatives within Cash App. Responsibilities include collaborating with various teams, developing prototypes, and driving strategic roadmaps.
As a Machine Learning Engineer at Kalepa, you will lead the framing, development, and scale deployment of machine learning models. You will process large datasets, transforming structured and unstructured data into insights about business risks. The role includes collaboration with Product Management and Software Engineers while working in a two-week sprint.
As a Senior Applied Scientist at Chewy, you will lead the deployment of machine learning and data science to enhance shopping experiences, develop new models, and influence product and engineering strategies. You will mentor junior scientists and present research findings to business leaders.
As a Machine Learning Engineer at ZS, you will build and monitor model pipelines, enhance ML engineering platforms, implement ML Ops, and write production-ready code. You will collaborate with teams to deliver projects, participate in scrum meetings, and contribute to evaluating new technologies.
As a Machine Learning Engineer at ZS, you'll build and monitor model pipelines, scale algorithms for large datasets, implement ML Ops, write production-ready code, and collaborate with teams to deliver AI-enabled solutions in healthcare. You'll also research new technologies and contribute to the enhancement of ML engineering platforms.
As a Principal Machine Learning Engineer, you will lead the technical roadmap for Snap's Ad Marketplace, designing and scaling machine learning models to enhance ad efficiency, collaborate with teams on machine learning strategies, and ensure operational excellence throughout the system.
The Machine Learning Engineer will focus on enhancing search relevance and personalization on Instacart's platform by developing and optimizing machine learning models. Collaboration with cross-functional teams is vital to create scalable solutions while also contributing to research and thought leadership.
As a Machine Learning Engineer at JPMorgan Chase, you will design and develop machine learning systems, preprocess datasets, research algorithms, and support workflows for experiments and model deployments. You will transform prototypes into deployable models and develop applications based on business requirements.
As a Machine Learning Engineer, you will be responsible for leading the development and deployment of machine learning models to assess business risks. You will analyze large data sets from various sources to derive insights and work closely with product and software teams in an agile environment.
In this role, you will develop AI/ML strategies to enhance customer support, lead the development of natural language processing systems, and collaborate with other teams to integrate ML capabilities into Canva's product offerings.
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