Top Senior Machine Learning Jobs

Lead and grow a machine learning team to build predictive models and ML features that drive revenue, retention, and product decisions. Partner with product and engineering, conduct exploratory analysis, design experiments, mentor engineers, and communicate insights to stakeholders.

Develop and scale machine learning systems to enable AI coaching, collaborate across teams for member insights, and contribute to architectural decisions.

The role involves enhancing a search-based question-answering platform through ranking features, algorithm frameworks, and performance metrics while collaborating with various teams to solve engineering challenges.

Lead and direct multidisciplinary teams to research, develop, test, integrate, and demonstrate advanced signal processing, optimization, and machine learning algorithms for radar, electronic warfare, and sensor systems. Oversee modeling/simulation, algorithm T&E, customer engagement, and technical briefings for defense and intelligence applications.

Develop, validate, and implement machine learning models using big-data tools and cloud platforms. Partner with engineers and product managers to translate analytics into production products, analyze large numeric and textual datasets, and communicate findings to drive business decisions for commercial banking portfolio forecasting.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

The Staff Applied AI Engineer will develop decision intelligence systems using machine learning and optimization, focusing on improving planning decisions and operational efficiency. Responsibilities include building models for revenue attribution, designing decision-support systems, and ensuring security in AI-driven capabilities.

The role involves deploying machine learning to enhance Chewy's advertising solutions, developing models for product ranking and prediction, and collaborating with product leaders. Responsibilities include leading new models, publishing research, mentoring, and driving technical strategies.

Lead WHOOP's strategy for transforming sensor data into real-time intelligence, managing teams, delivering features, and driving technical direction in machine learning and embedded systems.

Manage a team of ML engineers to build and optimize Affirm's economic decisioning engine using advanced ML techniques. Collaborate across teams, provide technical leadership, and mentor engineers while driving a cohesive long-term ML strategy.

As a Senior Machine Learning Engineer, you'll develop and optimize models for Chewy's Sponsored Ads to enhance product selection and advertising effectiveness. You will collaborate with cross-functional teams, lead model deployment, and publish research to elevate machine learning applications while mentoring junior scientists.

As a Staff Machine Learning Engineer, you'll enhance credit products through advanced modeling techniques, data analysis, and ML operations, supporting robust decision-making processes.

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Senior Machine Learning Engineer designs and develops ML systems, collaborates with teams to meet analytical needs, and optimizes large-scale ML solutions while setting monitoring and best practices.

Lead development, validation, and deployment of statistical and AI/ML models for credit and operational risk. Perform stochastic and spread analysis, oversee model documentation and MDLC compliance, collaborate with auditors and regulators, operationalize models with production teams, and share ML/NLP expertise across teams.

Contribute to machine learning model design, training, and evaluation for fraud detection. Communicate findings, develop metrics, and support production ML workflows while ensuring compliance and model governance.

Lead the development of healthcare data products using machine learning. Design models, collaborate with teams, and mentor others in statistical methods.

The AI Solutions Architect develops ML solutions, integrates them into systems, collaborates with stakeholders, and reviews code while maintaining technical architecture.

Lead modelling and analysis roadmap for FX products: forecast and monitor FX volatility, optimise trade execution with statistical/ML models, run customer and profitability analyses, and partner with product, trading, risk, and engineering to translate insights into trading and product decisions.

The role involves developing machine learning systems for Mars atmospheric modeling and multi-modal data fusion, contributing to autonomous science in space missions.

Responsible for validating payment network models, including fraud and AML. Engage with stakeholders, improve model accuracy, and leverage innovative technology for data analysis.

As a Senior Applied AI Engineer, you will develop and deploy AI/ML solutions for semiconductor processes, design software for large datasets, and drive innovative research to improve manufacturing efficiency.

Develop and deploy machine learning solutions for autonomous vehicles, mentoring engineers and collaborating on model implementations.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.