Top Machine Learning Jobs in Seattle, WA
As a Threat Analyst, you will analyze malware and detection tickets, improve detection capabilities, and assist internal teams with threat inquiries. You will work with binary files, conduct reverse engineering, and manage false positive detections, ensuring product detections match company standards.
As a Senior Machine Learning Engineer at Atlassian, you will develop and implement advanced machine learning algorithms with a focus on forecasting. You'll work collaboratively with various teams to build scalable models, guide junior engineers, and communicate complex concepts clearly to stakeholders, ensuring business impact and leveraging AI/ML applications.
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.
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The Senior Staff Scientist will develop hybrid AI applications optimized for quantum computing, lead a team of PhD scientists, collaborate across various technical teams, and engage with clients to identify valuable quantum applications. Responsibilities include developing quantum algorithms, integrating them with AI models, and influencing a multi-year Quantum AI roadmap at IonQ.
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.
You will develop and build machine learning models to detect fraudulent activity and assess risks in international money transfers, ensuring models meet latency and uptime requirements and collaborating with data scientists and engineers.
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 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 Principal Engineer, Machine Learning / AI will drive technical capabilities in ML and AI across multiple teams, mentor data scientists, lead technical standards, and advocate for best practices. The role involves hands-on development of ML/AI products and collaboration across various business units to enhance systems and products.
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.
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