Top Machine Learning Jobs in Miami, FL

Leads enterprise AI enablement and intelligent automation, overseeing use-case intake, prioritization, delivery, governance, adoption, and value realization. Establishes the AI operating model, builds literacy and training programs, manages automation and AIM teams, sets responsible-AI guardrails, tracks adoption metrics, and aligns investment with enterprise transformation priorities. Requires executive stakeholder leadership, portfolio governance, team development, and experience scaling AI or automation capabilities in complex organizations.

Develops strategic relationships and revenue growth with universities and higher-education research institutions. Owns the complete sales cycle, from prospecting and discovery through negotiation and closing, while meeting quotas and forecasting revenue. Creates territory and account plans, translates complex software and computing requirements into NVIDIA solutions, and collaborates with solution architects, product teams, developer relations, business units, and channel partners. Requires consultative technology sales expertise and understanding of AI, accelerated computing, and research environments.

Architect and scale cloud-based ML infrastructure supporting large-scale training, massive datasets, model development, and customer services. Own platform design, implementation, deployment, monitoring, reliability, cost optimization, and usability. Collaborate with data science, product, and operations teams, solve complex distributed-systems challenges, and mentor engineers while driving technical innovation.

Leads enterprise manufacturing AI, machine learning, and Industry 4.0 initiatives across multiple plants. Develops and deploys solutions for predictive maintenance, process and quality optimization, energy efficiency, throughput, and OEE improvement. Establishes scalable data and AI platforms, governance, and MLOps standards while integrating industrial data sources. Leads and mentors data science teams, prioritizes projects, allocates resources, partners with cross-functional manufacturing stakeholders, and presents strategic recommendations and business cases to executives.

Manage paid social campaigns and full-funnel strategies across Meta, LinkedIn, TikTok, Pinterest, Snapchat, and other paid channels. Oversee client accounts, analyze performance, identify growth opportunities, build client relationships, and collaborate with SEO, creative, and analytics teams. Contribute to thought leadership, coach associates, maintain quality standards, and explore automation, AI, and LLM search visibility initiatives.

Own the strategy, execution, customer success, and go-to-market for Oscilar’s Device and Behavior product. Lead development of SDKs, signal pipelines, behavioral biometrics, agentic identity signals, data networks, foundation-model capabilities, and analyst experiences. Partner with sales and customers to drive adoption, shape product positioning, and deliver a device intelligence and digital identity platform for fraud, onboarding, authentication, and risk decisions.

Supervise actuarial predictive modeling initiatives for insurance pricing, portfolio management, and planning. Collaborate with actuaries, data scientists, underwriters, and management to develop, validate, govern, and implement models. Establish assumptions, loss adjustments, usage guardrails, monitoring practices, and model documentation. Support regulatory filings, improve team workflows, contribute to strategic projects, and mentor staff in actuarial and technical skills.

Develop and maintain pricing and predictive models for credit insurance products. Analyze claims, loss ratios, portfolio performance, profitability, credit risk, and economic scenarios. Recommend pricing actions, support forecasting and reserves, evaluate underwriting strategies, and partner with underwriting, finance, claims, data science, and technology teams. Ensure model governance, documentation, and actuarial standards compliance.

Staff-level ML and agent systems engineer responsible for production model lifecycles, multi-step agentic systems, evaluations, retrieval and context engineering, and model cost and latency optimization. The role owns technical direction for Code Understanding products, improves model and agent quality, establishes evaluation and monitoring standards, mentors engineers, collaborates with customers, and delivers reliable AI-powered developer experiences at enterprise scale.

Designs, builds, and operationalizes enterprise AI, generative AI, machine learning, and agentic AI solutions. Develops integrations, orchestration services, reusable tooling, deployment pipelines, monitoring, and governance controls. Partners with architecture, platform, data, and product teams to deliver scalable, secure, compliant AI capabilities across the organization.

Designs and governs enterprise AI architecture, including generative AI, agentic workflows, RAG, orchestration, integrations, governance, security, compliance, and AI operations. Establishes scalable reference architectures, platform strategies, responsible AI guardrails, lifecycle management, monitoring, and cost controls. Partners with enterprise architecture, engineering, data, and product teams to drive secure AI adoption across cloud services, APIs, and enterprise platforms.

Owns the strategy, roadmap, requirements, backlog, positioning, and lifecycle execution for proprietary software products. Partners with engineering, UX, QA, architecture, data operations, and project management teams in an Agile environment. Conducts market and competitive analysis, supports product launches, creates AI prototypes, develops client-facing content, and contributes to RFP responses. Requires strong technical, product leadership, communication, prioritization, and stakeholder-management skills.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Build rigorous ROI analyses, value models, and business cases that translate AI ranking performance into revenue, margin, and cost-to-serve outcomes. Present analyses to CFOs, procurement teams, and other economic buyers; support sales pursuits; create reusable value-selling frameworks; tailor models to customer economics; and collaborate with product, data science, and customer teams to validate benchmarks and deployment results.

Own the full Global System Integrator partner lifecycle, including sourcing, agreements, joint go-to-market motions, enablement, delivery planning, and performance optimization. Build relationships across major GSIs such as Accenture, Deloitte, Bain, BCG, Slalom, and IBM. Collaborate with sales, product, and engineering teams to generate partner-sourced and influenced pipeline and revenue. Develop the GSI strategy, playbook, and operating processes for Sequen’s growing AI business.

Drive revenue retention and account growth across a portfolio of advertising clients. Responsibilities include developing account growth plans, managing forecasts and pipelines, identifying upsell and cross-sell opportunities, fostering product adoption, delivering data-driven campaign insights, leading QBRs, and coordinating Analyst, AdOps, Product, and Creative teams to resolve issues and achieve client outcomes.

Own the strategy, roadmap, packaging, pricing, design partnerships, and go-to-market launch of brightfin’s AI-native FinOps and ITFM product pillar. This individual contributor role will define the MVP, validate market demand, secure initial revenue, and scale the offering toward meaningful ARR. The leader must have extensive AI product leadership experience, direct ITFM/TEM/FinOps expertise, enterprise governance knowledge, and proven ownership of pricing, positioning, sales enablement, and commercialization.

Own strategic enterprise customer relationships, driving adoption, retention, measurable value, and expansion. Lead success reviews and executive engagements, translate supply chain challenges into solution strategies, build prototypes in Lyric Studio, train customer teams, coordinate forward-deployed engineers, partner with Sales on growth opportunities, and relay customer needs to Product and Engineering. The role requires deep supply chain expertise, technical fluency in modeling, planning, or AI/ML, and strong executive relationship skills.

Lead research and development of generative AI and recommendation solutions for Netflix promotional assets and content discovery. Responsibilities include tracking LLM research, developing summarization and LLM-as-judge systems, training and evaluating models, optimizing generated content for audience impact, partnering with engineering teams, defining ML roadmaps, and communicating technical strategies to stakeholders.

Leads innovation and enterprise solution strategy for healthcare payment integrity, developing scalable platforms using AI, automation, analytics, and data technologies. Engages senior clients, supports strategic pursuits, shapes transformation roadmaps, and builds partnerships. Oversees solution architecture, enterprise system development, prototyping, governance, performance metrics, and commercialization. The role also mentors cross-functional teams and translates complex healthcare payer challenges into differentiated, market-ready solutions.

Manage post-sales relationships with strategic customers, drive adoption and business outcomes, coordinate technology delivery projects, oversee customer issues and escalations, facilitate customer meetings and Quarterly Business Reviews, communicate customer needs internally, and track customer status and KPIs. The role supports financial institutions across North America and partners with technical, threat analysis, data science, product, and engineering teams.

Leads the software engineering organization responsible for scalable, reliable applications and systems integrating hardware, embedded software, edge computing, cloud infrastructure, and machine learning. Sets technical strategy, develops engineering leaders, drives product delivery, establishes engineering standards, and ensures operational excellence across national-scale deployments. Partners with Product, Deployment, Data Science, and executive leadership to align roadmaps, resolve risks, and build high-performing distributed teams.

Drive 100% new-business sales for Conga’s enterprise commercial solutions. Prospect, develop, manage, and close B2B SaaS opportunities while building territory, account, and opportunity plans. Partner with sales engineering, marketing, customer success, professional services, and other teams to deliver tailored solutions. Exceed revenue and quota targets, cultivate strategic partner relationships, communicate complex technology value, and sell revenue lifecycle management solutions including CPQ, CLM, document generation, and e-signature products.

Lead product strategy, roadmap execution, discovery, and delivery for Records Request Management and FOIA solutions. Define AI-enabled capabilities such as document discovery, automated redaction, classification, workflow optimization, and self-service. Partner with engineering, design, security, compliance, legal, sales, and customer teams to deliver secure, compliant products for federal and regulated public-sector customers. Translate FOIA and records-access requirements into product outcomes while supporting adoption, growth, and market expansion.

Develop complex healthcare reports, ETL solutions, databases, and Power BI dashboards for LTSS and Dual Eligible programs. Analyze multidimensional data, ensure governance and accuracy, identify operational improvements, and deliver actionable insights to leadership. The role translates business requirements into scalable reporting solutions, collaborates with clinical, operational, data engineering, and IT teams, and leads testing, process automation, visualization, and large cross-functional data projects.