Machine Learning Scientist
Design, train, and evaluate autoregressive and non-autoregressive speech synthesis models. Drive research on multi-modal architectures and collaborate with linguists to optimize TTS frontend behavior.
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Design, train, and evaluate autoregressive and non-autoregressive speech synthesis models. Drive research on multi-modal architectures and collaborate with linguists to optimize TTS frontend behavior.
The role involves developing novel Machine Learning and Deep Learning methods for medical image analysis, including segmentation, detection, and outcome prediction, while ensuring these methods are scientifically rigorous and clinically meaningful. Responsibilities also include publishing findings in top-tier venues and collaborating with clinicians to translate research into validated outputs for production engineering and regulatory submissions.
You will help design, implement, test, and refine novel elements of a machine learning architecture built from the ground up to optimize the properties of small molecule drugs. You will also continually improve the robustness of our existing code base and apply our pipeline to new drug targets.
Conduct innovative research at the intersection of weather prediction and machine learning to improve forecast performance. Partner with engineering teams to transition research advances into scalable, operational systems.
Develop and deploy multimodal deep learning models integrating imaging, genomic, and clinical data to advance oncology diagnostics. Collaborate with cross-functional teams to scale machine learning workflows and translate prototypes into validated, production-quality tools.
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You will architect and execute machine learning solutions, including the development of LLMs and AI agents to automate complex data analytics workflows. Additionally, you will lead the AI stack roadmap, establish model governance standards, and mentor team members to drive business growth.
The Staff Machine Learning Scientist will lead the development and deployment of personalization products and recommender systems to improve customer engagement. This role involves defining technical roadmaps, mentoring team members, and collaborating with stakeholders to ensure scalable and high-performance ML solutions.
Innovate and develop machine learning algorithms to maximize advertising performance and ROI. Collaborate with data engineers to write production-ready code and prototype new algorithmic pipelines.
The role involves owning end-to-end machine learning systems for forecasting, including model development, deployment, and monitoring. You will also build AI-assisted development workflows and partner with cross-functional teams to translate business needs into technical roadmaps.
The scientist will design and develop innovative machine learning solutions, specifically focusing on generative models and LLM-based evaluators. They will lead end-to-end ML development and partner with cross-functional teams to integrate these models into business applications.
Lead the user understanding charter by leveraging multimodal signals and LLM techniques to build a foundation for ad targeting, ranking, and bidding. Partner with cross-functional teams to define data strategy and implement rigorous evaluation frameworks for production ML systems.
Design and productionize causal machine learning systems to optimize marketplace decisions across various business verticals. Develop frameworks for counterfactual evaluation and uplift modeling to improve consumer lifecycle value, promotions, and search ranking.
You will develop and deploy predictive machine learning models to identify fraud, waste, and abuse within a large-scale healthcare claims warehouse. This role involves establishing modeling practices, collaborating with subject matter experts, and ensuring model output provides actionable evidence for investigators.
The role involves owning end-to-end machine learning systems for forecasting, including development, deployment, and monitoring. You will also build AI-assisted development workflows and partner with cross-functional teams to translate business needs into technical roadmaps.
The role involves owning end-to-end machine learning systems for forecasting, including model development, deployment, and monitoring. You will also build AI-assisted development workflows and partner with cross-functional teams to translate business needs into technical roadmaps.
You will build and prototype supervised machine learning models to predict campaign delivery outcomes, replacing existing simulation engines. Additionally, you will partner with ML engineers to deploy these models at scale while ensuring they are interpretable for sales and media-planning stakeholders.
Develop and innovate machine learning algorithms to optimize advertising performance and ROI. Collaborate with data engineers to implement novel algorithms into production code and iterate based on data insights.
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The Applied Machine Learning Scientist will innovate and develop ML algorithms to maximize advertising performance and ROI. They will also write production-ready code and collaborate with Data Engineers to implement and test novel algorithms.
You will lead the development of advanced machine learning models and human-in-the-loop systems to optimize customer operations and query resolution. You will also provide technical leadership within the ML discipline, mentoring team members and steering technical strategy across product squads.
Design and implement deep learning architectures for 3D volumetric medical imaging and develop survival models for time-to-event prediction. Optimize large-scale training pipelines on cloud GPU infrastructure and contribute to research publications.
Develop and deploy production-ready ML and AI systems to optimize pricing, underwriting, and claims processes. Build end-to-end agentic workflows and measurement frameworks to improve business decision-making across the insurance value chain.
Lead the research and development of health trajectory models and next-best-action algorithms to improve member outcomes. Provide technical leadership and mentorship to scientists while collaborating with product and engineering teams to productionize ML models.
Design and develop innovative ML solutions to enhance promotional writing and content discovery for Netflix members. Lead end-to-end development from research and model training to integration into business platforms.
Lead the design and deployment of advanced real-time ML models to detect financial crime and suspicious user behavior. Provide technical leadership and mentorship within the ML discipline while collaborating with cross-functional product squads.
Lead the development and deployment of advanced ML models to enhance search and discovery for the Monzo Co-pilot. Act as both a technical leader and individual contributor to build scalable, responsible AI solutions for over 15 million customers.
Design, build, and operate scalable machine learning and AI systems to power business-critical decision making and clinical operations. Own the end-to-end ML lifecycle from data engineering and model training to deployment and production monitoring.
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Lead the end-to-end development and deployment of personalization products and recommender systems to improve book discovery. Define the technical roadmap, mentor other scientists, and collaborate with stakeholders to align ML strategy with business goals.
Lead the end-to-end development and deployment of personalization products and recommender systems to improve book discovery. Define the technical roadmap, mentor other scientists, and collaborate with stakeholders to align AI strategy with business goals.
Develop and deploy machine learning solutions to address high-impact societal challenges while collaborating with cross-functional teams and social sector organizations. Mentor junior researchers and contribute to academic research through publications in leading conferences and journals.
Define and drive the ML technical roadmap for Live Ads, focusing on forecasting, targeting, and yield optimization. Collaborate across teams to architect and deploy large-scale ML solutions that improve ad quality and performance.
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