Top Machine Learning Jobs in Pensacola, FL

Conduct empirical AI safety research with mentor guidance, owning projects from hypotheses and controlled experiments through analysis and technical writing. Build and debug evaluation harnesses, agent environments, datasets, monitoring methods, and post-training experiments. Investigate model failures, alignment, deception, misuse, multi-agent risks, and evaluation reliability. Produce reproducible code, experiment logs, research analyses, and papers for potential submission to leading machine learning conferences.

Own enterprise sales across new and existing accounts, leading consultative, ROI-driven sales cycles from discovery through close. Develop account plans, build executive relationships, collaborate with Solutions and Forward Deployed Engineers, forecast pipeline, maintain CRM discipline, lead business reviews, represent the company at industry events, and relay customer insights to shape the product roadmap.

Develop and support software, automation tools, dashboards, and alarms for cloud infrastructure, cost attribution, and cloud efficiency. Collaborate with cross-functional teams and senior engineers to design reliable systems, APIs, databases, tests, and AI agents. Contribute to architecture and automation strategies while maintaining strong security, communication, and delivery practices.

Own strategic ISP customer accounts across onboarding, adoption, value realization, retention, renewals, and expansion. Serve as an executive trusted advisor, lead business reviews, mitigate churn, and partner with Sales, Product, Marketing, and Engineering. Help scale Plume’s Customer Success function through improved playbooks, tooling, engagement models, customer advocacy, and standardized methodologies.

Leads AF Group’s AI and emerging technology strategy, translating business priorities into prioritized use cases, business cases, roadmaps, and measurable outcomes. Directs cross-functional delivery from experimentation through production adoption, coordinating security, platform, application, data, and Center of Excellence partners. Evaluates generative AI, machine learning, and automation technologies; manages budgets, resources, change management, operational readiness, adoption, and value realization. Supervises employees and develops organizational AI capabilities.

Develop graduate-level Applied AI course materials, including lessons, labs, case studies, assignments, rubrics, projects, readings, templates, and videos. Design practical activities using LLMs, RAG, AI agents, automation, APIs, and evaluation tools. Collaborate with learning designers and university faculty, explain complex concepts to nontechnical learners, maintain academic quality, and update content as AI tools and regulations evolve.

Product Counsel will advise product, data science, engineering, sales, and marketing teams on legal and regulatory issues involving digital identity, biometrics, AI, privacy, consumer protection, fraud prevention, and financial technology. Responsibilities include product lifecycle counseling, commercial agreements, policies, privacy governance, regulatory engagement, customer diligence, legal training, and AI-enabled legal workflows. The role requires translating complex legal requirements into practical business guidance while supporting global market expansion and responsible innovation.

Leads technology consulting engagements involving technology, data, and AI strategy; software and architecture assessments; analytics and business intelligence; program delivery; business cases; product roadmaps; and due diligence. Manages client stakeholders, workstreams, deliverables, priorities, and junior team members while developing strategic insights, resolving complex issues, supporting sales, and delivering large-scale technology programs.

Leads the design, implementation, and evolution of enterprise security capabilities across federal cloud and hybrid environments. The role engineers Zero Trust architectures, FedRAMP High controls, identity and access management, encryption, logging, vulnerability management, monitoring, and incident response. Responsibilities include supporting ATO authorization, continuous monitoring, risk remediation, security assessments, and secure adoption of AI-enabled technologies. The position requires collaboration with cloud, infrastructure, DevSecOps, compliance, and operations teams.

Drives business transformation and strategic change initiatives by developing transformation strategies, improving processes and organizational design, managing change adoption, engaging senior stakeholders, coordinating cross-functional projects, delivering training, and tracking benefits realization. The role manages transformation projects from planning through post-implementation review while ensuring alignment with business objectives, timely delivery, budget adherence, and successful organizational adoption.

Own the Lighthouse healthcare platform backlog from problem discovery through launch, including specifications, acceptance criteria, prioritization, QA, release readiness, and outcome measurement. Collaborate with engineering, design, data science, clinical operations, compliance, security, and legal teams to deliver safe clinical and agentic capabilities, predictive-model workflows, and care-team productivity improvements. Establish continuous discovery, define product metrics, coordinate agile delivery, and ensure human-in-the-loop clinical review.

Develop fraud detection and identity-risk machine learning models from problem definition through production deployment. Responsibilities include investigating fraud patterns, exploratory analysis, feature engineering, model training and evaluation, production-quality Python and PySpark development, monitoring model and feature drift, and presenting analytical recommendations. The role requires collaboration with data scientists and engineers while addressing privacy, explainability, validation, governance, and real-world fraud-modeling challenges such as class imbalance and delayed labels.

Leads AML transaction monitoring optimization, including rule testing, threshold tuning, scenario design, and alert reduction. Drives FIU automation and workflow improvements, evaluates AI-enabled compliance tools, and partners with Product, Engineering, Data, Operations, and vendors on monitoring infrastructure and integrations. Supports scalable compliance controls across new products, jurisdictions, and transaction volumes while maintaining regulatory alignment and detection effectiveness.

Manage enterprise metadata, business glossaries, data catalogs, and end-to-end data lineage for a federal case management modernization program. Configure governance and metadata platforms, integrate data sources and pipelines, establish standards and workflows, monitor metadata quality, support compliant data sharing, develop governance metrics, document procedures, and train data stewards and business users.

Performs hands-on cybersecurity and AI engineering, defines and documents functional and technical requirements, converts requirements into Jira stories, validates application features, and collaborates with customers, developers, systems engineers, and AI stakeholders. Evaluates AI architectures, model performance, integration tradeoffs, and emerging AI/ML applications for enterprise software. Requires active TS/SCI with polygraph clearance, U.S. citizenship, a bachelor’s degree, and 15+ years of experience.

Develop and maintain scalable automated testing frameworks for web applications, backend services, and distributed microservice architectures. Design risk-based test strategies, perform API, performance, load, and security testing, maintain automated quality gates, investigate defects, and conduct root cause analysis. Collaborate with architects, product managers, and QA engineers on release readiness, quality improvements, test coverage, and system integrity across complex data and UI workflows.

Develops data quality checks, metadata standards, and AI use-case inventories for HHS. Cleans and integrates complex datasets, applies machine learning and NLP for automated tagging and classification, evaluates AI governance risks, and produces reporting datasets, dashboards, and recommendations. The role requires translating ambiguous federal policy and reporting requirements into repeatable analytical workflows while collaborating with product, design, engineering, and government stakeholders.

Develop and deploy machine learning and LLM-based solutions for cybersecurity challenges. Responsibilities include analyzing complex datasets, building classification and NLP models, optimizing prompting, embeddings, RAG, and fine-tuning techniques, designing evaluation methodologies, and integrating models into scalable production systems. The role requires collaboration with cybersecurity researchers, software engineers, data engineers, and product managers.

Own the authorization optimization product roadmap, improving legitimate transaction approval rates and recovered merchant revenue. Define technical requirements, APIs, data models, integrations, and issuer-specific decisioning strategies. Partner with engineering, data science, sales, solutions, and customer success to deliver fraud-aware authorization improvements involving retries, 3DS, decline recovery, and payment routing. Manage partnerships with payment ecosystem providers, quantify opportunities using issuer and BIN intelligence, and communicate product strategy and performance to stakeholders.

Leads the design, implementation, and support of complex, scalable software components and distributed systems. Provides technical leadership through architecture decisions, mentoring, code and design reviews, troubleshooting, and engineering standards. Partners with product, quality, architecture, and DevOps teams on secure cloud-native solutions, CI/CD, observability, performance, releases, and platform modernization. Participates in hiring and communicates technical risks and tradeoffs to stakeholders.

Owns the AI strategy, roadmap, and initiative portfolio for assigned business areas. Identifies and prioritizes AI opportunities, translates business needs into compliant AI solutions, and partners with stakeholders, IT, and AI teams to deliver outcomes. Builds less complex AI agents using approved tools, supports technology adoption, monitors KPIs, and uses analytics, feedback, and market trends to guide continuous improvement and investment decisions.

Leads Parexel’s HEOR modeling service line, overseeing client engagements, project delivery, profitability, business development, team leadership, and strategic growth. Advises senior clients on evidence generation, cost-effectiveness analysis, health policy, and market access. Develops AI-enabled HEOR methodologies using machine learning, natural language processing, analytics, and predictive modeling. Partners with scientists and health economists, represents the organization externally, and manages service-line strategy, budgets, forecasts, revenue, and performance.

Leads biostatistical activities for Phase II–III clinical trials, from protocol design through reporting and regulatory submission support. Responsibilities include statistical analysis planning, sample size calculations, SAP development, TLF review, database lock support, safety reporting, regulatory responses, and oversight of programming or CRO work. Collaborates with cross-functional clinical teams and uses SAS or R for analyses, modeling, simulation, exploratory work, and quality control. Coordinates statistical activities across studies and applies advanced statistical and machine learning methods.

Leads statistical activities for Phase II–III clinical trials from protocol design through reporting and regulatory submissions. Develops statistical analysis plans, sample-size calculations, and reviews tables, listings, and figures. Oversees internal programmers and CRO contributions, applies SAS and R for analyses and quality control, and collaborates with clinical, data management, programming, and regulatory stakeholders. Coordinates statistical activities across studies and applies advanced statistical, machine learning, and modeling methods to support drug development.

Develop and standardize analytical methods for inferring residence, displacement, and poverty from mobile network operator data. Assess data quality, write technical specifications and tests, guide operator engineering teams, tune statistical methods, and balance accuracy with implementation constraints. Design privacy-preserving analyses, improve data security practices, train internal teams, and support international workshops and emergency-response programs.