Top Remote Machine Learning Jobs in Miami, FL

Drafts and prosecutes U.S. and international patent applications focused on quantum computing and emerging technologies. Responsibilities include working with inventors and engineers, preparing Office Action responses, managing patent portfolios, advising on patent strategy, and developing client relationships. Requires substantive quantum computing patent experience, USPTO registration, a technical degree, a JD, and at least three years of patent preparation and prosecution experience.

Leads Sophos’s Americas MSP channel strategy, revenue growth, partner productivity, and operating performance. Oversees recruitment, onboarding, enablement, retention, distribution relationships, recurring-revenue forecasting, strategic negotiations, and program optimization. Builds and coaches direct and matrixed teams while influencing product, pricing, investments, and partner-program decisions. Uses performance data and market intelligence to improve activation, adoption, retention, expansion, and return on investment across cybersecurity managed-service offerings.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Serve as lead legal advisor to product, engineering, and technology teams on AI, software, cloud, privacy, cybersecurity, intellectual property, and technology transactions. Develop AI governance and responsible-use policies, assess regulatory and ethical risks, negotiate technology and AI vendor agreements, advise on IP and data workflows, monitor global technology regulations, and train employees. The role requires significant legal experience, active bar membership, AI and privacy expertise, and the ability to influence executive and cross-functional stakeholders.

Leads analytics and reporting for Microsoft’s Cloud Solutions Provider authorization ecosystem. Develops actionable insights, dashboards, data visualizations, and self-service reporting; improves data quality, governance, standardization, and efficiency. Partners with engineering, AI, operations, and compliance teams to automate workflows, identify risks, evaluate program outcomes, and recommend improvements. Presents findings to senior stakeholders and translates business needs into technical requirements and scalable analytical solutions.

Own and scale the company’s global privacy and data protection program. Advise product, engineering, sales, marketing, security, and executives on privacy laws, data transfers, DPAs, AI governance, security commitments, incident response, and regulatory requirements. Manage privacy assessments, data inventories, notices, training, outside counsel, and vendor relationships. Partner with Security and GRC on audits, certifications, breach response, government requests, and customer obligations while building scalable processes and eventually a privacy team.

Designs and operates production data infrastructure, ETL/ELT pipelines, APIs, containerized AWS services, and graph-based systems. Responsibilities include relational, document, and graph database architecture; data quality and lineage; CI/CD automation; and integration of blockchain, financial, and investigative data. Partners with R&D, data scientists, and investigations teams to deliver production software for federal and commercial clients.

Lead the Personal Loans portfolio strategy, quantitative analysis, risk-based pricing, deal economics, and profitability initiatives. Manage a distributed analytics and portfolio team across New York and Israel, align strategies with partners, and collaborate with Risk, Product, Capital Markets, and Engineering. Translate complex credit and financial analysis into executive recommendations while optimizing customer conversion, risk-adjusted yield, margins, and lifecycle outcomes.

Lead a portfolio of technology-enabled continuous improvement initiatives for internal operations and DoD customers. Manage product backlogs, write user stories, define roadmaps, gather requirements, and facilitate Agile, Scrum, SAFe, and PI planning activities. Drive Splunk analytics, dashboarding, alerting, AI, ML, automation, proactive monitoring, and predictive analytics solutions. Ensure stakeholder alignment, measurable operational improvements, and compliance with DoD security requirements while maintaining an active Secret clearance.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Develop and productionize machine learning models and predictive analytics using Python, Databricks, PySpark, SQL, and Delta Lake. Build scalable data science workflows, resolve healthcare data quality and entity-resolution issues, and apply Master Data Management practices. Partner with engineering, product, analytics, and business teams to deliver governed, HIPAA-compliant solutions. Perform exploratory analysis, feature engineering, model evaluation, deployment, documentation, and data lineage management for healthcare and member engagement initiatives.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Design, develop, and deploy scalable AI applications and services across the OneStream platform. Build production machine learning solutions, troubleshoot full-stack issues, participate in technical design sessions, and collaborate with cross-functional teams. The role involves applying forecasting, anomaly detection, and natural language processing while maintaining reliable, well-documented code and continuously learning emerging AI technologies.

Lead CrowdStrike Finance & Accounting AI transformation: define operating model and governance, prioritize AI use cases, oversee POC-to-production delivery, drive enablement and change management, measure benefits realization, and report outcomes to executives.

Leads technical pre-sales and foundational implementation engagements for SailPoint SaaS solutions. Discovers customer requirements, maps them to product capabilities, delivers proof-of-value implementations, explains architecture and best practices, and collaborates with sales, product, services, and customer success teams. Develops AI and agentic technology solutions for demonstrations and customer problems, while serving as a technical and consultative advisor to customers, partners, and colleagues.

Lead technical customer engagements for strategic accounts, supporting sales, solution design, foundational implementations, and proof-of-value deployments. Discover requirements, map them to SailPoint solutions, educate customers on architecture and best practices, collaborate across sales, product, professional services, and customer success, and develop AI- and agentic-technology solutions for demonstrations and customer outcomes.

Forward Deployed Engineers support sales and customer engagements by discovering requirements, designing and implementing foundational SaaS solutions, delivering proof-of-value implementations, and educating customers on architecture and best practices. They collaborate with sales, product, professional services, and customer success teams; use AI and agentic technologies to solve customer problems; lead technical engagements; document requirements; and develop reusable demonstration solutions. The role may require up to 15% travel.

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Develops and productionizes deep learning and machine learning perception models for robotics and recycling sortation. Responsibilities include experimenting with neural network architectures, designing computer vision solutions, conducting statistical experiments, deploying successful models, collaborating with data, modeling, and cloud infrastructure teams, and improving ML infrastructure.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead Sardine’s fraud product portfolio, setting vision and roadmap across device intelligence, behavioral biometrics, and machine learning. Manage product managers and partner with engineering, data science, risk operations, marketing, and sales. Drive fraud detection performance, reduce false positives and customer friction, monitor emerging threats, and scale zero-to-one products into enterprise-ready solutions for payment and fraud-prevention customers.

Leads the enterprise data strategy, builds and scales the Data & Analytics team, and oversees data warehouse modernization, migration, governance, KPI standardization, and data quality. Partners with executives and cross-functional teams to convert data into actionable insights, operational improvements, predictive analytics, and AI-enabled workflows. The role requires hands-on Python, SQL, cloud, machine learning, and ETL expertise, plus strong leadership and communication skills.

Leads a data science team and personally drives analyses, experimentation, and product analytics to identify patient experience improvements. Partners with Product, Engineering, Research, and Data Engineering teams to develop product features, evaluate business and product performance, guide product planning, and translate statistical findings into actionable recommendations. Manages and develops analytical talent while applying data storytelling, A/B testing, marketplace metrics, and retention, conversion, engagement, and churn analysis.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Leads Lyra Health’s AI/ML engineering roadmap, scales and mentors machine learning teams, and drives production-grade systems for clinical applications. Responsibilities include people leadership, quarterly planning, technical architecture, design reviews, model governance, ML SDLC oversight, and deployment of reliable microservices on Kubernetes. The role partners with product, data science, and clinical stakeholders while ensuring safety, operational excellence, cloud scalability, and compliance for sensitive healthcare data.