Top Remote Machine Learning Jobs in Miami, FL

Lead Felix's global pricing strategy and infrastructure. Define monetization trade-offs, run advanced pricing experiments and elasticity research, partner with Finance on unit economics, and collaborate with Engineering to build automated/ML-driven pricing engines while keeping pricing transparent and user-friendly.

Use advanced analytics and ML to design and monitor credit risk models, optimize underwriting and credit strategies, partner with Engineering/Product/Compliance, oversee portfolio performance and regulatory alignment, and lead cross-functional initiatives to balance growth, compliance, and risk mitigation.

Lead the SDL and Cash Line ML teams, developing innovative machine learning models to improve lending solutions and expand credit access. Collaborate with cross-functional teams to drive product strategy and enhance model performance, while mentoring a team of ML scientists.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Role involves assisting with machine learning model improvement through tasks like data labeling, content evaluation, and participation in testing activities.

As an AI/ML Data Contributor, you will perform data labeling, content evaluation, and user-based testing to improve machine learning models, working both remotely and on-site.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

The Senior Product Manager will oversee the strategy and development of telematics data products, manage cross-functional teams, and ensure product viability and market alignment through customer insights and technical fluency.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

Lead the Data + ML Platform team to design, build, and operate scalable data and MLOps infrastructure. Drive platform strategy, enable ML experimentation-to-production workflows (model registry, feature stores, drift monitoring, experiment tracking), modernize streaming and batch pipelines, and scale the team while partnering cross-functionally to deliver measurable outcomes.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

Lead and coach Agile software teams, facilitate Scrum ceremonies, manage timelines, risks, and stakeholder communication, and support delivery of AI-enabled solutions across client engagements in a distributed consulting environment.

Lead fraud detection and mitigation for a conversational BNPL product. Define fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, collaborate on ML models and decisioning workflows, and coordinate SARs and compliance reporting.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, pricing models, vintage and NPV analyses, executive reporting, model integration and testing, and explore alternative data to optimize approval rates and portfolio health.

Lead fraud detection and mitigation for a conversational Send Now Pay Later product: define first-party fraud typologies, own repayment and chargeback analytics, manage fraud KPIs, design operational policies, integrate ML and decisioning tools (Taktile), and coordinate SARs and compliance reporting.

Lead credit analytics for the Send Now Pay Later product: build and optimize valuation, vintage and NPV models; manage credit policies, portfolio monitoring, and NPL reporting; integrate and test scoring models with engineering/data science; and research alternative data to improve predictive performance.

Lead fraud detection and mitigation for a conversational BNPL product: define fraud typologies, analyze repayment/chargeback trends, own fraud KPIs, design policies, collaborate on ML models and decisioning workflows, and coordinate SARs with Compliance.

Lead fraud risk for a conversational lending product (SNPL): define first-party fraud typologies, analyze repayment and chargeback trends, own fraud KPIs, design automated/manual blocking policies, coordinate ML/rules with central Fraud and Data teams, and liaise with Compliance on SARs and loan abuse.

Lead quantitative credit analytics for a Send Now Pay Later (SNPL) product: build and maintain credit policies, pricing and NPV models, vintage analysis, portfolio monitoring, model integration/testing, and alternative data evaluation to optimize approval rates and manage portfolio health.

Own vision and roadmap for an AI-powered claims decision-support and auto-adjudication platform. Lead a team of product managers and cross-functional squads, translate complex claims policies into product logic, partner with business, engineering and data science, drive delivery, adoption, and measurable business impact, and communicate strategy to senior leadership.

Lead design and scaling of a unified fraud and risk platform. Own roadmap, fraud metrics, SQL-based analysis, A/B testing, real-time detection models, and cross-functional delivery to balance customer experience and risk mitigation.

Lead and build the full demand generation function: inbound, outbound-assist, ABM, field, and digital. Own pipeline metrics (MQLs, SQLs, pipeline contribution), run integrated enterprise campaigns, manage marketing tech stack (CRM, MAP, intent, analytics), and align closely with Sales on ICP, messaging, and pipeline quality.

Lead delivery of advanced analytics and investigative support for federal programs. Manage multiple concurrent projects, schedules, costs, risks, personnel, vendors, and stakeholder communications to ensure quality, timely contract-aligned deliverables.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.