Top Machine Learning Jobs in Tampa, FL

Own BI product management for Quote-to-Cash and Order-to-Cash processes. Partner with finance, sales, legal, product, and engineering teams to identify operational issues, translate financial data needs into BI and AI/ML opportunities, define PRDs and roadmaps, and ensure quoting, billing, deal structuring, and revenue recognition processes are accurately represented in downstream data products.

Develop and maintain production machine learning models, build scalable training and serving technologies, optimize real-time and batch ML pipelines, and monitor model performance and drift. The role involves deep neural networks, recommendation systems, automated retraining, ML research, engineering excellence, and communicating technical concepts to diverse audiences. Candidates need 6+ years of industry ML experience, strong coding skills, and experience deploying neural networks at scale.

Designs, deploys, administers, and optimizes enterprise Splunk UBA/UEBA environments. Develops behavioral baselines and machine learning models, normalizes identity-centric data using Splunk CIM, and integrates anomalies with Splunk Enterprise Security and SOAR workflows. Collaborates with SOC and insider-threat teams to detect credential misuse, account takeover, and lateral movement. Monitors platform health, troubleshoots issues, and documents configurations, detection logic, and playbooks.

Designs, engineers, tunes, and maintains security detections, correlation rules, behavioral analytics, and CI/CD pipelines for detection content. Supports network security, access management, incident response, risk assessments, security architecture, and complex troubleshooting. Leads incident recovery, root cause analysis, testing, technical escalations, vendor coordination, and collaboration with security operations, fraud, threat intelligence, infrastructure, and engineering teams.

Leads enterprise-wide Finance transformation, advising the CFO and Finance Leadership Team while modernizing operating models, processes, technology, data, and governance. Oversees organizational redesign, shared services, location strategy, automation, AI adoption, finance systems, continuous improvement, program governance, change management, and executive stakeholder alignment. Builds and leads a transformation office, establishes roadmaps and success metrics, manages risks and benefits, and develops high-performing teams.

The Data Scientist translates business questions into statistical and machine learning solutions, including data collection, cleaning, modeling, automation, and deployment. The role develops predictive and inferential models, creates data visualizations, presents findings to business leaders, and partners with business and technology stakeholders. Responsibilities also include analytics consulting, needs analysis, training, support, and applying data science techniques to increasingly complex business problems.

Leads and develops a data science team applying statistics, machine learning, causal inference, and AI to business problems. Establishes standards for experimentation, model governance, validation, responsible AI, and reproducibility. Partners with business, engineering, BI, and IT stakeholders to prioritize analytics initiatives, translate business questions into solutions, deploy models into production, and communicate actionable insights to executives and nontechnical audiences. Oversees career development, stakeholder adoption, and strategic alignment.

Design and build software tooling, firmware, automation, data pipelines, and compute infrastructure supporting semiconductor design, verification, manufacturing, and post-silicon validation. Collaborate with hardware and EDA teams to improve silicon development, yield, performance, and quality. Translate requirements into production solutions, troubleshoot complex hardware-software issues, participate in design and code reviews, and mentor junior engineers.

Coordinates technical and programmatic information across defense acquisition program offices, consolidates portfolio status, analyzes trends, tracks risks, supports technology roadmaps, and briefs senior leadership. Represents the PEO in external engagements and funding activities while overseeing requirements, systems engineering acquisition milestones, cloud-native deployment considerations, and alignment with DoD acquisition frameworks.

Lead technical client onboarding, migrations, solution design, integrations, data orchestration, troubleshooting, and project delivery for Movable Ink’s AI-powered personalization platform. Partner with clients and internal teams to implement custom workflows, APIs, webhooks, and data solutions. Conduct training and workshops, provide product expertise, advise on roadmap improvements, and support long-term client success across email and mobile marketing programs.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Lead and grow a data science team building production machine learning models. Oversee the full model lifecycle, including data sourcing, feature engineering, training, deployment, and monitoring. Coach technical staff, manage planning and executive communication, investigate fraud patterns, improve model performance, and deliver dependable production code for real-time decisions. Present analyses that guide data strategy, product direction, operations, marketing, and sales.

Leads customer-facing technical delivery from demonstrations and requirements discovery through architecture, implementation, testing, and production launch. Builds AI-driven agents, analytical products, predictive modeling workflows, and data pipelines; integrates solutions with client CRMs, consumer applications, and varied data sources. Partners with client technical teams, presents to senior stakeholders, and feeds field learnings back to the core platform team. Requires occasional travel and strong Python, TypeScript, architecture, cloud, and communication skills.

Design, develop, secure, modernize, and support scalable omnichannel APIs for customer-facing web, mobile, contact center, partner, and enterprise applications. Improve API security, resiliency, performance, observability, testing, and reliability. Collaborate with architecture, security, cloud, product, operations, and engineering teams; lead technical delivery, mentor engineers, develop reusable patterns, and provide Tier 3 production support. Apply AI-assisted engineering practices and contribute to API lifecycle management and continuous improvement.

Lead the architecture, development, integration, and validation of AI-enabled autonomy for UAS, drone swarms, robotic platforms, and C2 systems. Develop real-time decision-making, sensor fusion, navigation, multi-agent coordination, and edge AI capabilities. Build simulation and digital-twin environments, conduct hardware-in-the-loop and flight testing, integrate tactical systems, and improve resilience against contested environments. Lead engineering teams, manage AI/ML governance and deployment, support DevSecOps and cybersecurity compliance, and advise mission stakeholders.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

Leads business analysis for complex technology initiatives by eliciting and documenting requirements, translating business needs into user stories and solution specifications, facilitating stakeholder workshops, and supporting QA/UAT. Performs process analysis, gap assessments, impact analysis, and production issue triage. Acts as a subject matter expert and helps define AI, automation, analytics, and conversational AI use cases while partnering with technology, data, architecture, and business teams.

Early-career Data Scientist supporting supply chain transformation through machine learning, forecasting, statistical modeling, data preparation, dashboards, and AI solutions. The role addresses inventory optimization, demand forecasting, production planning, delivery performance, and cost reduction. Responsibilities include developing analytical datasets and workflows with Python and SQL, evaluating models, integrating enterprise data, supporting cloud-based analytics, and communicating insights to business stakeholders in a manufacturing environment.

Leads complex enterprise technology initiatives, including ERP implementations, BI, data analytics, AI, and systems integration projects. Manages planning, scope, timelines, resources, budgets, risks, dependencies, stakeholder communications, executive reporting, and cross-functional delivery across Product, Engineering, Data, and business teams. Drives process improvements and ensures projects meet business objectives, customer outcomes, and delivery commitments.

Own end-to-end SaaS implementations from solution alignment through configuration, data preparation, training, UAT, go-live, and handoff. Serve as the primary customer and project lead, managing timelines, risks, dependencies, stakeholders, and readiness. Configure workflows and platform settings, troubleshoot data and configuration issues, coordinate cross-functional teams, and identify implementation improvements. The role requires strong customer communication, project management, SaaS configuration, data handling, and business workflow analysis skills.

Own the technical sales cycle for Databricks consulting engagements, including discovery, architecture design, solution scoping, estimation, proposals, demos, proofs of concept, workshops, and statements of work. Design lakehouse, data engineering, analytics, governance, security, and AI architectures. Partner with sales, Databricks, alliance, and delivery teams while ensuring effective handoffs into implementation.

Own complex post-sale technical relationships from onboarding through adoption and renewal. Lead implementations, integrations, configurations, and security reviews; advise strategic customers on identity, access, device trust, and SaaS security. Partner with Customer Success and cross-functional teams to drive customer value, manage risks, support expansion, create scalable resources, and mentor team members while serving as an escalation point.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.