Top Machine Learning Jobs in Jacksonville, FL

Lead partner marketing with consulting and systems integrators to drive joint GTM plans, co-marketing programs, repeatable partner collateral, customer stories, partner communications, and measurable pipeline growth.

Define and execute Americas logistics and warehousing strategy; lead multi-site DC operations, inbound/outbound logistics, carrier management, trade compliance/imports, P&L oversight, WMS/TMS/ERP optimization, and AI/automation adoption. Requires cross-regional enablement and ~25-40% travel.

Lead operationalization of AI strategy by implementing scalable AI platforms, standards, and governance. Identify and prioritize high-impact AI and analytics use cases, drive end-to-end delivery into production, embed AI into business processes, manage AI teams, mentor practitioners, and evaluate emerging AI/GenAI technologies to ensure responsible, secure, and measurable business impact.

Lead the architecture, implementation, integration, and optimization of Oracle EPM Planning solutions. Design planning, budgeting, forecasting, modeling, security, metadata, and reporting frameworks; configure Oracle EPM modules; and apply AI-driven forecasting capabilities. Lead requirements workshops, testing, deployment, stakeholder presentations, and pre-sales activities. Mentor consultants and developers while advising finance and executive stakeholders on enterprise planning transformation initiatives.

Design and operate large-scale, AI-native cloud infrastructure (especially Kubernetes/AKS). Improve service quality, automate incident prevention/remediation, accelerate engineering productivity, and integrate AI tools into development workflows.

The Product Marketing Manager will develop go-to-market strategies, create compelling messaging, perform market research, and collaborate with product and sales teams to position Oscilar's AI risk platform effectively.

Identify business challenges and translate them into AI initiatives; architect AI solutions using appropriate models, frameworks, and infrastructure; guide data science and engineering teams through proof-of-concept development and deployment; mitigate bias and model drift through monitoring; and communicate an AI vision aligned with business goals.

Develop and optimize scalable, low-latency bot threat detection, request risk detection, and fraud prevention products. Responsibilities include implementing features, improving existing functionality, designing architectures, testing and deploying code, troubleshooting complex customer issues with Level 3 Support, and analyzing web and mobile platform data. The role requires performant web API development, knowledge of HTTP and common data formats, and integration of machine learning tools and LLMs.

Lead and deliver complex, cross-team AI product programs, drive agent-first SDLC adoption, ensure integration and operational readiness of AI workflows, define metrics, communicate risks and status, and standardize TPM best practices across Product and Engineering.

Analyze microbiome and longitudinal clinical data, develop biomarkers and microbiome metrics using statistical and machine learning methods, and create visualizations, reports, protocols, and study reports. The role supports research, product development, scientific publications, proposals, and clinical studies while collaborating independently with microbiome experts in a remote-first startup environment.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Manage the development and implementation of Evio Compass, an analytic product identifying patient risks, while guiding cross-functional teams to drive customer success and enhance ML/AI product features.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Leads data science strategy across Mexico and Brazil, manages and mentors a distributed team, and remains hands-on building and deploying machine learning models. Establishes modeling standards, infrastructure, delivery practices, and technical roadmaps while partnering with credit leadership on underwriting, valuation, impact measurement, and P&L analysis. Requires strong applied machine learning expertise, prior data science leadership, business communication skills, and understanding of credit or underwriting.

Design and deliver secure, high-performance microservices and APIs. Develop backend services in Java and Python, integrate ML components, build front-end service layers, deploy containerized applications to cloud platforms, and collaborate in Agile teams to ensure scalable, test-driven solutions.

Develop and optimize machine learning and statistical models for fraud detection and anti-money laundering. Analyze large datasets to identify fraudulent patterns, build scalable data pipelines and features, evaluate model performance, and collaborate with engineering, product, and operations teams. Communicate insights to technical and non-technical stakeholders while maintaining data privacy and security compliance. The role offers significant ownership in building Oscilar’s early machine learning stack within a remote-first startup.

Own the technical architecture, strategy, and roadmap for an autonomous construction robotics stack spanning localization, planning, controls, and safeguarding. Make build-versus-reuse-versus-buy decisions, design safety systems, guide integration and field validation, establish shared technical foundations across autonomy programs, and mentor engineers. The role requires architecting and shipping production autonomous systems, strong compiled-language software skills, broad systems judgment, and 10+ years of relevant experience.

The Senior Machine Learning Researcher will design experiments, research new algorithms, and collaborate on deploying models for computer vision and robotics applications.

Leads enterprise sales strategy and revenue growth for AI-powered eDiscovery, legal technology, compliance, analytics, and data intelligence solutions. Builds pipelines, manages complex consultative sales cycles, develops executive client relationships, expands strategic accounts, and positions responsible AI adoption. Partners with product, operations, legal, security, marketing, and executive teams on solution development, pricing, contracts, implementation, and market expansion across corporations, law firms, government, and regulated industries.

As an AI Applications Engineer, you will bridge AI research and implementation, driving experiments, building infrastructure, and releasing products to improve user experience and metrics.

Leads technical solution development for military and federal health capture and proposal efforts. Designs secure cloud, DevSecOps, EHR modernization, interoperability, data, and analytics architectures; develops technical volumes, graphics, compliance matrices, staffing estimates, demonstrations, and presentations. Ensures security and compliance alignment, supports pricing strategy, collaborates across capture and delivery teams, and mentors architects and subject-matter experts.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.

Oversee development, validation, monitoring, and governance of consumer credit risk models used for loss forecasting, credit decisioning, regulatory reporting, and risk management. Apply statistical, econometric, and machine learning methods to PD, LGD, and EAD models; support CECL, stress testing, and macroeconomic scenario analysis. Assess model performance, data quality, and compliance while communicating findings to senior leaders, auditors, regulators, and other stakeholders.

Serves as the technical and business advisor for Verint’s Open CCaaS platform, selling CX automation solutions to C-suite customers. Builds executive relationships, communicates ROI, leads cross-functional product and sales teams, identifies expansion opportunities, and delivers thought leadership. Requires expertise in AI, data science, contact center operations, data architecture, and cloud platforms, with approximately 30–50% travel.