Top Machine Learning Engineer Jobs in Seattle, WA
The Machine Learning Engineer will create models to drive user and advertiser value at Snap. Responsibilities include evaluating technical trade-offs, conducting code reviews, and building scalable products quickly while maintaining quality. Collaboration and mentorship are key aspects of the role.
As a Staff Machine Learning Engineer, you will design, build, and productionize machine learning models to tackle various business challenges. Collaborating with product and engineering teams, you will focus on data processing, improving service performance, and sharing knowledge through discussions and presentations.
The Machine Learning Engineer will design, build, and deploy large-scale machine learning systems, collaborating with cross-functional teams to personalize user experiences at Dropbox. Responsibilities include evaluating ML system performance, working with large-scale data systems, and participating in on-call rotations as needed.
The Computer Vision Machine Learning Engineer will develop ML algorithms and core pipelines, train deep learning models for real-time applications, and collaborate closely with multidisciplinary teams to create autonomous robotic solutions. Responsibilities include dataset curation and proposing innovative solutions for complex real-world challenges.
Responsible for training, tuning, and evaluating models using Deep Learning and Large Language Models. Collaborate with AI engineers to design and maintain ML pipelines. Proficient in crafting ML models and leveraging machine learning frameworks such as SKLearn, XGBoost, PyTorch, and Tensorflow.
As a Machine Learning Engineer, you will build and scale ML model pipelines, implement MLOps, write production-ready code, and collaborate with clients and global teams to deliver AI solutions. You will also engage in research to evaluate new architecture patterns and technologies.
As a Machine Learning Engineer, you will design and build large-scale ML systems, collaborate with cross-functional teams, and enhance user experiences at Dropbox. Your role will involve evaluating and deploying machine learning solutions, impacting millions of users.
The Machine Learning Engineer at Snap Inc will create models that drive user and advertiser value, evaluate technical tradeoffs, perform code reviews, and build scalable products. Strong collaboration and mentorship skills are essential, along with a solid understanding of machine learning algorithms.
Featured Jobs
As a Machine Learning Engineer at Snap Inc, you will develop models that provide value to users and advertisers. You'll perform code reviews, evaluate technical tradeoffs, build scalable products, and solve complex problems collaboratively with teams, ensuring quality and innovation.
The Computer Vision and Machine Learning Engineer will develop innovative solutions using state-of-the-art techniques, maintaining core libraries, integrating computer vision methods with ML, and collaborating with teams to benchmark system performance.
The Machine Learning Engineer will build, optimize, and deploy machine learning models for identity resolution and ads attribution. They will collaborate with cross-functional teams, perform code reviews, and stay updated on machine learning technologies while ensuring high-quality scalable products.
As a Senior Applied Scientist, you will lead the Sponsored Advertising team at Chewy, deploying machine learning and data science to enhance product discovery and customer engagement. Responsibilities include developing predictive models, collaborating with product leaders, mentoring junior scientists, and communicating research insights to executive leadership.
Work as an Applied Machine Learning Engineer at Atlassian, responsible for developing and implementing cutting-edge machine learning algorithms, training models, and collaborating with product and engineering teams to integrate AI functionalities into Atlassian products.
As a Principal Machine Learning engineer at Atlassian, you will drive the development and implementation of cutting edge machine learning algorithms, collaborating with various teams to integrate AI functionalities into Atlassian products. Responsibilities include designing architectures, conducting experiments, and guiding emerging ML engineers.
Seeking a Senior Principal Machine Learning Engineer to lead the development and deployment of advanced machine learning algorithms and system architecture. Responsible for training complex models, integrating AI functionalities into products, and mentoring ML engineers.
Senior AI Engineer responsible for training and tuning models using Deep Learning Machine Learning Models, Large Language Models, data engineering, and evaluation frameworks. Working on optimizing networks to better serve applications with a highly novel approach.
The Machine Learning Engineer III will design, develop, and implement machine learning models for various applications while ensuring reliable and scalable cloud architectures. Key responsibilities include using IaC tools for cloud resource management, handling containerization and orchestration for applications, and providing technical mentorship to the data science team.
The Staff Machine Learning Engineer at Snap Inc will create models to drive value for users and advertisers, evaluate technical tradeoffs, conduct code reviews, build scalable products, and work collaboratively with partners. Candidates should have strong technical skills in machine learning and mentoring abilities.
As a Principal Machine Learning Engineer, you will drive the technical roadmap for Snap's Ad Marketplace, focusing on the design, implementation, and optimization of machine learning models to enhance ad delivery and spending efficiency. Collaboration with cross-functional teams and advocacy for best practices in scalability and operational excellence are key aspects of this role.
The Principal Machine Learning Engineer will design and implement machine learning components and services, build a training framework, optimize model performance using GPUs, and develop an AutoML platform. The role involves collaboration across teams to meet product requirements and advocating for best practices in system availability and scalability.
As a Principal Machine Learning Engineer on the Ad Ranking team, you will drive the technical roadmap, design and implement machine learning models for ad optimization, collaborate with various teams to align on strategies, and advocate for best practices to enhance performance and scalability.
As a Machine Learning Engineer, you will analyze opportunities, propose ideas, train and evaluate ML models, run experiments, and deploy solutions to production. You will contribute to ML architecture and be part of the ML community at Stripe. Responsibilities include improving performance, evaluating systems, and ensuring model quality. Minimum requirements include 5 years of end-to-end ML development experience, an advanced degree in a quantitative field, and proficiency in Python, Scala, and Spark.
As a Machine Learning Engineer at Stripe, you will design and build scalable ML platforms, develop deep learning architectures for payment entities, and collaborate with data scientists to enhance product features using machine learning. The role focuses on deploying advanced ML applications and optimizing infrastructure for rapid experimentation.
Lead Machine Learning Engineer responsible for developing and maintaining Hulu's recommendation algorithms. Collaborate with various teams to achieve strategic personalization goals. Lead algorithm development, optimization, and roadmap setting for product areas. Responsibilities include algorithm development, feature engineering, collaboration with stakeholders, and maintaining development best practices.
As a Senior Machine Learning Engineer at Atlassian, you will work on developing and implementing cutting-edge machine learning algorithms, training models, and collaborating with product and engineering teams. You will design system architectures, conduct model evaluations, and guide junior ML engineers to integrate AI functionalities into Atlassian products.
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