Top Machine Learning Jobs in Orlando, FL

Leads the development of partner enablement programs for Databricks and Snowflake ecosystems. Establishes strategies, governance, stakeholder relationships, learning pathways, workshops, bootcamps, champion networks, and readiness frameworks for technical and business audiences. Translates data, AI, analytics, and lakehouse use cases into scalable learning experiences, aligns programs with partnership growth objectives, measures engagement and effectiveness, and continuously improves initiatives based on partner feedback and business impact.

The Enterprise Account Executive will drive revenue growth by managing complex sales cycles, closing deals with Fortune 500 companies, and understanding both technical and business needs.

Leads complex technical programs supporting government and defense missions, managing scope, schedules, budgets, risks, customer relationships, and multidisciplinary teams. Provides technical direction across software development, cloud architecture, data engineering, operations research, analytics, and decision support. Oversees modeling, optimization, machine learning, dashboards, and executive recommendations while engaging senior government stakeholders. Supports proposals, capture activities, technical reviews, and continuous improvement initiatives.

Collects and analyzes performance data, identifies trends, evaluates program effectiveness, and develops reports and visualizations for stakeholders. The role standardizes datasets, improves data collection and analytical methods, and supports data-driven decisions. It requires statistical analysis, data manipulation, visualization, and familiarity with machine learning and predictive analytics. The position is contingent on contract award and requires the ability to obtain and maintain an active Secret Clearance.

Leads business insights and analytics for Rocket Pharma’s gene therapy portfolio, with emphasis on rare cardiology. Responsibilities include disease modeling, patient-identification analytics, forecasting, market research, real-world data integration, analytics platform development, and market-development strategy. The role partners cross-functionally with IT, vendors, field teams, and external analytics providers while translating fragmented data into strategic recommendations and ensuring compliant use of analytics and market research investments.

Builds a talent network of experienced data scientists for potential future AI evaluation projects. Responsibilities may include creating grading criteria, evaluating AI-generated or human-produced data science work, writing evidence-based justifications, applying consistent judgment, and incorporating reviewer feedback. Candidates should have professional data science experience, strong Python and SQL skills, expertise in statistical modeling, machine learning, experimentation, causal inference, and excellent technical communication.

Designs and supports scalable cloud data warehouses for CMS healthcare fraud, waste, and abuse analytics. Responsibilities include data modeling, healthcare interoperability, secure HIPAA-compliant governance, lineage, testing, CI/CD, automation, workflow scheduling, and technical architecture. The role integrates claims and healthcare domains using Snowflake and industry standards while collaborating with stakeholders, documenting solutions, and leading warehouse project delivery.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Lead integrated paid media strategy and execution across channels, modernize media planning with technology and data, manage agency/vendor relationships and multimillion-dollar budgets, build media capabilities and teams, and deliver executive insights to optimize ROI using AI, automation, and advanced measurement.

Leads Yahoo’s Detection Engineering team within Threat Detection and Response. Responsibilities include developing cybersecurity detection strategy, managing detection engineers, building and maintaining detection rules, supporting investigations, conducting threat hunting and purple-team activities, integrating threat intelligence, and applying data science and AI to identify adversaries. The role also guides sprint delivery, researches emerging threats, and collaborates with security leadership, incident response, insider threat, and advanced cyber threat teams.

The Senior Data Scientist will analyze large-scale customer data, investigate behavioral questions, design and automate studies, and translate findings into actionable recommendations. The role includes maintaining analytics frameworks, documenting methodologies, writing white papers, and communicating insights across the company. Candidates should be independent, comfortable with ambiguity, and experienced with SQL and Redshift. Python or R, machine learning, Spark, A/B testing, and cross-functional experience are preferred.

Lead product design for Fetch’s Receipt & Rewards experience, connecting receipt capture, account linking, recognition, matching, and rewards. Define design strategy for complex, AI-enabled systems; improve usability, accessibility, trust, and experience quality; and balance user needs, data quality, business goals, and technical constraints. Partner with Product, Engineering, Research, and Data Science, drive cross-functional alignment, shape multi-quarter initiatives, and mentor designers.

Lead the roadmap and delivery of an AI data platform supporting internal teams and external healthcare products. Manage ML and LLM platform workstreams across data ingestion, training, deployment, monitoring, and workflow optimization. Partner with AI engineers, researchers, data scientists, clinical leaders, and business stakeholders to define requirements, develop user stories, validate model performance, and turn proofs of concept into scalable production capabilities.

Build privacy and anonymization systems that detect and transform PII, credentials, secrets, and other sensitive information in data used for AI training. Develop detection methods combining rules, statistical models, classifiers, and LLMs; create production data-processing pipelines; evaluate privacy risk and retained utility; and ensure robustness against schema drift, unusual formats, leakage, and adversarial re-identification.

Provide legal support for commercialization and product development of an AI-powered ad tech platform: draft and negotiate commercial agreements, manage IP portfolio and complex IP litigation, advise on AI, data, and privacy matters, counsel product teams on compliance and IP protection, and develop automated legal workflows.

Leads client services and cross-functional delivery teams supporting enterprise software implementations. Oversees end-to-end project execution, client relationships, business-process transformation, stakeholder education, requirements documentation, and ongoing value delivery. Applies revenue growth management expertise across pricing, trade promotions, assortment, or supply planning, while collaborating with technical teams on AI, machine learning, and analytics solutions.

Own product marketing for Gladly’s Agent Harness and AI Core platforms. Develop technical positioning, messaging, launch strategies, sales enablement, competitive intelligence, and narrative assets. Translate AI agent behavior, evaluation, steering, and measurement into credible messaging for CX leaders and technical buyers. Manage tier-one launches end to end while balancing two product areas as a senior individual contributor with minimal oversight.

Leads and develops a perception and machine learning engineering team building computer vision, sensor fusion, tracking, detection, and scene-understanding capabilities for autonomous systems. Owns roadmap planning, technical decisions, delivery, model development and deployment workflows, field readiness, hiring, performance management, and cross-functional execution with autonomy, embedded, data, hardware, product, programs, and field operations teams.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

Develop and deploy machine learning models for manufacturing use cases including predictive quality, machine failure prediction, and time-series pattern discovery. Work directly with customers to scope problems, validate solutions in live deployments, and translate successful analyses into product features. Collaborate with engineering, product, and customer success teams while applying statistics, optimization, generative AI, and agentic AI to deliver end-to-end solutions.

Analyzes complex healthcare data to identify trends, develop statistical and machine learning methodologies, and produce actionable insights. Builds dashboards and reports, supports product and business decisions, promotes data literacy, and collaborates with cross-functional teams. The role also ensures analytics practices comply with healthcare privacy, governance, security, and regulatory requirements, including HIPAA.

Leads commercial growth execution as the CCO’s operating partner, orchestrating go-to-market programs across Sales, Marketing, Customer Success, Partnerships, and Operations. Establishes execution frameworks, operating rhythms, accountability systems, KPI dashboards, and performance reporting. Aligns cross-functional leadership, scales sales motions, identifies capability gaps, removes execution barriers, and drives measurable revenue, customer, and market growth initiatives.

Owns product vision, strategy, roadmap, and execution for Yahoo Search monetization across traditional and AI-powered search. The role optimizes sponsored search relevance, ranking, placement, coverage, revenue, and user experience while developing new advertising formats for conversational and generative experiences. Responsibilities include experimentation, marketplace analysis, performance measurement, partner collaboration, and close work with engineering, data science, analytics, and design teams.

Lead end-to-end data science and AI projects: translate business problems, prepare large datasets, build and deploy predictive/prescriptive and generative AI models (including LLM fine-tuning and prompt engineering), communicate insights to stakeholders, and promote responsible, explainable AI practices across consulting engagements.

Design and implement enterprise AI architectures spanning GenAI, machine learning, RAG, agentic workflows, data pipelines, APIs, and production deployments. Build Python prototypes and AI services, define governance and evaluation frameworks, integrate models with enterprise platforms, and guide engineering teams through implementation. The role requires hands-on expertise with LLM applications, orchestration frameworks, model lifecycle management, monitoring, security, and scalable production AI systems, preferably in financial services.