Top Senior Machine Learning Jobs in Tampa, FL

Build and lead Precision Neuroscience’s partnership function across the life sciences and healthcare ecosystem. The role owns strategic partnership pipelines, structures and negotiates complex technology and scientific collaboration agreements, advises leadership on deal strategy, translates technical work into commercial narratives, and establishes partnership processes for an early-stage neurotechnology company.

Drive enterprise revenue growth across South Florida by acquiring new accounts, expanding the install base, managing the full sales cycle, developing territory plans, forecasting, building partner channels, and closing complex networking and security solutions. The role requires executive-level selling, quota attainment, technical business-value communication, pipeline development, and use of AI tools for prospecting, account planning, forecasting, and customer engagement.

Manages Pulmovant’s enterprise application portfolio, including validated GxP and clinical systems and core IT platforms. Oversees system performance, configuration, compliance, access, documentation, integrations, upgrades, and validation. Partners with Clinical, Regulatory, Quality, Finance, and HR stakeholders, manages vendors and an applications team, and leads continuous improvement, root-cause analysis, and application initiatives. The role also supports AI and machine learning governance, model validation, and responsible data practices.

Own a broad territory focused on acquiring net-new enterprise customers for SingleStore’s AI and data platform. Build self-sourced pipeline through outbound, account-based, partner, and market-education motions; engage executive and technical stakeholders; develop ROI and TCO cases; navigate complex technical, security, legal, procurement, and negotiation processes; partner with engineers to establish production workloads; and manage forecasting, qualification, CRM hygiene, and new-logo performance.

Lead enterprise AI security architecture, strategy, governance, and secure-by-design implementation across cloud, hybrid infrastructure, software, and AI/ML environments. Design security patterns for LLM hosting, agentic systems, vector databases, and inference endpoints; translate regulatory requirements into technical standards; review complex architectures; implement AI security guardrails and policy enforcement; advise engineering and product teams; and mentor teams while influencing senior stakeholders.

Leads data and analytics transformation strategy for major client programs, defining roadmaps, use cases, architecture direction, and operating models. Advises senior stakeholders, facilitates strategy workshops, aligns programs to KPIs and value frameworks, supports governance and risk management, contributes to proposals and pre-sales, and mentors consulting and analytics teams.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Source, develop, and close enterprise health system clients across a US territory. Build relationships with healthcare executives, launch and expand pilot programs, create account plans, meet revenue targets, and transition customers to Client Success. Collaborate with product, legal, marketing, support, and leadership; provide sales forecasts and pipeline reporting in HubSpot; influence the product roadmap; and represent Nabla at industry events.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead Tilt’s product design function across consumer financial products. Set design vision and quality standards, manage and grow a team of six designers and one researcher, build research capabilities, influence product strategy, scale the design system, advocate for users, and partner with Product, Engineering, Marketing, and executive leadership. Drive AI-enabled design practices and ensure product experiences deliver measurable user and business impact.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

Serve as a customer-facing fraud and identity expert across pre-sales, onboarding, and expansion. Evaluate customer risk profiles, design fraud strategies and identity workflows, advise on risk mitigation and verification optimization, and coordinate technical, regulatory, and operational launch readiness. Lead implementation milestones, go-live planning, and cross-functional resolution of deployment bottlenecks while helping enterprise customers maximize adoption and long-term value.

Own the strategy, roadmap, and growth of Ottimate’s new product initiatives across procurement, budgeting, spend planning, and contract management. Lead customer discovery, validation, MVP development, launches, and portfolio metrics. Manage product managers and designers, oversee Design and UX, and partner with engineering, data science, sales, marketing, and customer success to deliver coherent, market-ready products.

Leads technical support for VA healthcare AI citizen developers, developing and validating supervised, unsupervised, and reinforcement learning models. Builds synthetic healthcare data cohorts, designs secure cloud-based data science workflows, collaborates with federal stakeholders, interprets analytical results, mentors developers, and ensures model quality, documentation, privacy, governance, and regulatory compliance.

Build and scale production AI systems for Prophetic’s real estate intelligence platform. Responsibilities include developing agentic systems, data pipelines, inference workflows, evaluation benchmarks, geospatial processing, and machine learning applications across hundreds of millions of records. The role requires shipping reliable Python services, optimizing throughput and cost, integrating research into products, and collaborating with engineering and product teams.

Owns CareSource’s EDI platform vision, roadmap, backlog, and delivery. Translates healthcare, regulatory, and integration requirements into technical specifications; partners with engineering, architecture, QA, DevOps, trading partners, and business teams; coordinates releases and Agile delivery; monitors transaction performance, defects, SLAs, and platform telemetry; drives data quality, observability, automation, compliance, documentation, and continuous improvement across EDI capabilities.

Build and scale an international robotics data acquisition network across emerging markets. Source venues and strategic local agencies, optimize lead-generation funnels, evaluate deployment environments, coordinate hardware installation and calibration, and establish reliable data pipelines. Manage vendor training, SLAs, KPIs, verification, and anti-fraud controls while translating robotics and embodied AI data requirements into field operations. Requires international growth or field operations experience, partner management, technical data fluency, language skills, and frequent travel.

Lead enterprise payments architecture for card-present solutions, provide technical governance and guidance, integrate AI-enabled capabilities securely, develop and review production code, evaluate emerging technologies, and drive architecture decisions across product families.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead performance marketing data science initiatives focused on lead segmentation, bidding optimization, targeting, and marketing spend allocation. Develop and deploy production-ready machine learning systems, establish research and ML operations roadmaps, build monitoring frameworks, and identify high-impact opportunities. Partner with engineering, marketing, vendors, and executives while mentoring data scientists and machine learning engineers and promoting rigorous, maintainable, and reproducible practices.

Build and deploy AI agents, intelligent applications, scalable backend services, APIs, and full-stack solutions. Integrate large language models, AI services, data platforms, and external APIs into customer-focused products. Collaborate with engineering, product, and cross-functional teams while contributing to cloud-native applications, data pipelines, distributed systems, testing, deployment, and production operations.

Leads AI presales strategy, customer advisory, technical solution architecture, and team development. Translates business needs into AI use cases, prototypes, business cases, roadmaps, and repeatable offerings. Partners with sales, engineering, consultants, and technology vendors to support complex pursuits, executive briefings, demonstrations, proofs of concept, and AI business growth. Promotes responsible AI governance, tracks pipeline performance, develops thought leadership, and remains hands-on in high-impact customer engagements.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Leads enterprise AI strategy and operations by building AI product portfolios, agentic workflows, copilots, intelligent applications, and human-AI experiences. Partners with executives, engineering, data science, security, and business teams to prioritize opportunities, establish roadmaps, redesign workflows, drive adoption, govern AI initiatives, and measure business value. Builds and leads AI product management teams while overseeing organizational change and cross-functional portfolio governance.