Top Machine Learning Jobs in Tallahassee, FL

Design, build, and operate core AI capabilities and reusable model integrations for an enterprise platform. Integrate foundation models into production, optimize performance and reliability, prototype new techniques, and support scalable backend services and distributed AI systems in collaboration with cross-functional teams.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Lead and scale end-to-end data annotation operations: set quality standards, build and manage an in-house annotation team and vendors, translate research into annotation guidelines, implement QA systems, drive AI-assisted labeling, partner with ML/CV and product, and own metrics and reporting.

Own end-to-end product development for AI/ML revenue cycle solutions: define vision and roadmap, write specs and user stories, prioritize backlog, work closely with data scientists and engineers, drive agile delivery, ensure quality, and measure product performance with stakeholders.

Work on-site with portfolio companies to design, prototype, and deliver full-stack digital and AI solutions. Lead discovery, deployment, and post-launch iteration, ensure security/compliance, resolve technical issues, mentor teams, and drive enterprise integrations and adoption. Frequent domestic travel and stakeholder management required.

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

Sell Litify's AI-driven legal operating platform to law firms and legal departments. Manage full upsell motions, consult on AI adoption, deliver high-level demos to C-suite, meet sales targets, and articulate ROI of autonomous agents and AI integrations.

Lead and mature Omada's enterprise privacy program, manage HIPAA compliance and incident response, embed privacy-by-design across products, conduct privacy risk assessments and vendor due diligence, advise on consumer privacy and AI governance, support interoperability/HIE participation, and deliver privacy training and guidance across the business.

Design and evaluate causal inference experiments and causal ML models to measure product impact, optimize resource allocation, and inform support operations. Build, deploy, and iterate statistical/ML models, analyze tradeoffs, collaborate cross-functionally, and communicate insights to influence decisions and scale data science capabilities.

The Staff Machine Learning Engineer will lead ML systems development for personalization and ranking, design architectures, and mentor team members, ensuring reliable operations at scale.

Provide legal counsel on privacy, AI, identity, and advertising technology; embed privacy by design with product and engineering teams; draft and negotiate privacy provisions and DPAs; advise on cross-border transfers and SCCs; run privacy and AI risk assessments; support incident response; create scalable legal playbooks and AI-enabled workflows; represent Yahoo in industry standards bodies.

The Technical Product Marketing Manager will drive product marketing strategy, understand Socure's technology, craft technical narratives, and enhance internal and external communication through enablement materials.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

Design, optimize, and deploy deep learning models for customer behavior prediction. Perform feature engineering, implement research-informed architectures, scale training pipelines, collaborate with client teams, document findings, and uphold engineering best practices.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

Lead full-funnel marketing analytics and a small AI-augmented team to measure and optimize paid media and lifecycle journeys. Own test-and-learn experiments, attribution and incrementality frameworks (MTA, MMM), vendor evaluation, and partnership with ML to improve CAC, LTV, and channel efficiency. Translate results into actionable growth recommendations.

Lead product ownership for Advisor Experience, owning roadmap from discovery to delivery. Build integrations and AI features (Aspen AI, client portal), deliver advisor capacity and transition tools, work with engineering/design/data and external partners, and drive Client Excellence KPIs (Net Revenue Retention, NPS, advisor retention, transition success).

Lead and develop a team of five East Coast Enterprise Sales Leaders to drive new logo acquisition and account expansion. Build sales plans, manage pipeline from lead generation through close, recruit and coach leaders, and contribute to GTM strategy while reporting to the VP of Enterprise Sales. Remote-first role with occasional off-hours work.

Drive technical wins for enterprise financial institutions by scoping solutions, leading discovery (MEDDPICC), tailoring demos, building business cases, owning RFI/RFPs and POCs, and coordinating product/engineering to validate feasibility for fraud and financial crime prevention.

Lead government relations in the Western U.S. to drive adoption of AI-powered school bus safety solutions. Build relationships with municipal and state officials, school leaders, and law enforcement; advocate for legislative and regulatory changes; run grassroots campaigns; monitor policy developments; represent the company at hearings and events; and collaborate with Sales, Marketing, and Legal.

Own and scale delivery of complex AI data programs (LLM/ML products), ensuring scope, quality, timeline, and margin targets. Translate ambiguous problems into technical workstreams, establish governance, drive solution reviews, embed responsible AI practices, manage vendors, and lead cross-functional teams while partnering with BD and executive stakeholders.

Lead product vision and roadmap for Tekion's Automotive CRM, translate dealer and partner needs into product requirements, define AI/LLM-enabled CRM capabilities, collaborate cross-functionally to deliver SaaS CRM features, create product artifacts, measure success metrics, and prioritize initiatives to drive adoption and strategic account success.

Build and maintain ML and generative AI tooling, training and inference platform services, model evaluation and testing frameworks, and APIs to expose ML products. Deploy and manage applications across the AI/ML SDLC, mentor teammates, and write production-quality code daily.

Architect and implement scalable AI/ML platforms, pipelines, services, and APIs for an enterprise modernization program. Responsibilities include model training and deployment, MLOps, cloud infrastructure, multi-tenant and multi-region architecture, monitoring, optimization, responsible AI, documentation, dashboards, and third-party ML tool integration. The role guides agile teams while ensuring federal security, privacy, governance, compliance, performance, availability, and cost-efficiency requirements are met.