Top Senior Machine Learning Jobs in Jacksonville, FL

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Regional VP of Sales drives sales for Lirio, focusing on healthcare systems. Responsibilities include pipeline generation, relationship building, and strategic sales management.

Lead vision, strategy, and roadmap for Fetch's referral growth engine. Own end-to-end referral lifecycle, build incentives, experimentation, AI-driven personalization, and cross-functional initiatives to drive MAU growth and durable network effects.

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.

The role involves researching, developing, and implementing AI solutions, optimizing models, integrating AI into workflows, and collaborating with teams to enhance business efficiency.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

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.

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

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.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The role involves defining the vision and strategy of the Outreach AI Platform, prioritizing the roadmap, collaborating with engineering and data science teams, and engaging with customers to refine AI strategies.

Lead complex, cross-functional AI programs end-to-end: translate strategy into integrated plans, drive multi-team execution, mitigate risks (data, model, compliance), apply ML lifecycle practices, use Agile/kanban methods, manage budgets/vendors, communicate to senior stakeholders, and mentor other program managers to improve AI program standards.

Lead product analytics to improve user growth, engagement, retention, and revenue. Design and analyze A/B and multivariate experiments, perform funnel/cohort analyses, maintain KPIs and dashboards, ensure event tracking, leverage ML and AI tools for advanced analyses, and translate insights into product recommendations across cross-functional teams.

Design and lead end-to-end AI solution architectures, ensuring scalability, security, and compliance. Translate business and regulatory requirements into technical designs, evaluate tools/platforms, document architecture standards, coordinate technical teams, and support deployment and ongoing improvements.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Lead design, build, and operate an end-to-end Identity Platform for KYC/KYB, overseeing CIP, CDD, sanctions screening, and continuous risk monitoring. Drive AI-first automation to reduce manual reviews, mentor engineers, manage reliability and incidents, and represent technical solutions to customers and regulators. Partner cross-functionally to shape roadmap and ensure regulatory compliance and extensibility across jurisdictions.

Lead a team of safety engineers to define and execute AV safety strategy across development, simulation, testing, and deployment. Apply UL4600/ISO standards, develop safety cases, set safety metrics (SPI), manage safety plans and artifacts, train engineers, and coordinate with partners and stakeholders to validate ML models and ADS integration for safe public-road operation.

Lead product initiatives for football data analytics and AI experiences: define business cases, understand customer workflows, drive cross-functional squads, own in-product onboarding and customer success, and iterate quickly to deliver measurable outcomes like revenue and retention.

Lead product discovery, prioritize roadmaps, and deliver football data analytics and AI features. Work with design, engineering, analytics, and former NFL experts to build, onboard, and iterate products that drive revenue, retention, and customer success in a fast-paced startup environment.

Lead design and scaling of a unified fraud and risk platform. Define product strategy, own fraud metrics, run SQL-driven analysis and A/B tests, and partner with engineers and data teams to build real-time detection, identity verification, and transaction monitoring. Balance customer experience with risk mitigation and communicate impact to executives, legal, and partners.

Own and scale the customer entry-to-purchase lifecycle: design acquisition journeys, build and optimize welcome/abandon/lead conversion automations, implement personalization and gamification, partner cross-functionally, steward list health and deliverability, and run A/B and multivariate testing to improve conversion and engagement metrics.

Lead sales of Akamai's enterprise security portfolio across assigned Midwest accounts, develop and manage pipeline, position Zero Trust architectures, collaborate with internal security engineers and researchers, engage C-level stakeholders, and close new and expansion business.

Advise clients on antitrust eDiscovery compliance using machine learning and generative AI. Build and validate TAR/AI models (Epiq AI, Relativity, Reveal, Brainspace), craft LLM prompts, draft defensible protocols, train/transfer workflows to review teams, and support client-facing, pre-sales, and thought-leadership activities. Must manage multiple projects and meet deadline-driven schedules.

Lead technical pre-sales for large Oil, Gas & Energy accounts, define and implement Databricks-based data and ML/AI strategies, build technical champions, mentor teammates, and drive enterprise adoption through technical leadership and value selling.