Top Senior Machine Learning Jobs in Orlando, FL

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.

Lead global sales enablement strategy and programs to drive revenue, product adoption, and GTM readiness. Oversee product-aligned enablement teams, launch readiness, content and demo strategy, CRM and tool adoption, measurement frameworks linking enablement to outcomes, and integration of AI into enablement.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.

Lead a centralized Data Science & Engineering team to build scalable data pipelines, productionize ML/AI solutions, ensure data governance and reliability, partner with cross-functional stakeholders to prioritize initiatives, and drive platform improvements for analytics, personalization, and product features.

Lead design, build, and operation of data architecture, pipelines, and semantic layers. Manage sprint planning, DevOps metrics, data quality and monitoring, and MLOps enablement. Partner with stakeholders, coach engineers, track project plans, and ensure data availability, accuracy, and documentation.

Lead strategy and build 0->1 AI products that streamline complex healthcare workflows across providers, pharmacies, patients, and pharma partners. Own roadmap, requirements, metrics, and product performance; partner with engineering, data, clinical, and commercial teams to launch and iterate AI-enabled solutions that drive adoption and measurable business and patient outcomes.

Owns the design, development, training, and deployment of scalable machine learning models, pipelines, and production systems. Leads end-to-end ML workflows from data ingestion through model serving, contributes to ML platform architecture, reviews and writes pipeline code, and provides technical guidance to engineers and data scientists. Collaborates with data engineering, data science, and product teams while driving model improvements, debugging, and issue resolution.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Lead backend architecture and implementation for scalable, reliable cloud-hosted web products. Mentor engineers, set standards, integrate agentic AI coding tools, design systems applying ML to large datasets, and balance customer-facing features with technical debt and performance.

Lead end-to-end product areas that improve build speed, cost accuracy, margin, and throughput. Own strategy, roadmap, and execution for complex financial and operational data products, integrate AI/ML into workflows, write precise requirements, instrument metrics, run experiments, and drive cross-functional outcomes with construction, finance, sales, design, and engineering teams.

Lead the Contracts product roadmap for a B2B healthcare SaaS platform, applying deep reimbursement and managed care expertise. Partner with AI engineers to build contract-understanding models, drive adoption, iterate on workflows, create business cases, and coordinate cross-functionally with Legal, Finance, Sales, and SMEs to ensure compliant, revenue-aligned contract execution.

Lead engineering team to define and execute threat detection, platform, analytics, and automation roadmaps. Advance automated, AI-augmented detection and response across SIEM/EDR/NDR/SOAR and cloud environments, partner with Incident Response, and drive measurable risk reduction via metrics and team development.

Design and implement data-centric cybersecurity solutions: develop ML algorithms and automation for security tools; discover, parse, map, and transform legacy RMF artifacts into OSCAL; migrate and analyze security data; reproduce dashboards/workflows in eGRC; collaborate with Professional Services; produce migration assessments and reports.

Embed with customers to discover needs, design and implement production-grade integrations (APIs, data pipelines, event-driven workflows), deploy and troubleshoot solutions, train IT teams, and drive adoption and measurable business outcomes.

As a Senior Fullstack Engineer, you'll architect and build a high-concurrency auction engine, leveraging AI for enhanced user experiences and system reliability.

Lead the development of deep learning models for email data, optimize models, design evaluation frameworks, integrate products, and mentor junior researchers.

Lead strategy, roadmap, and delivery for Tekmetric's SaaS product for auto repair shops. Own user research, AI/ML product initiatives, cross-functional alignment, go-to-market coordination, and measurement of business outcomes. Train internal teams and iterate on features from concept through launch and optimization.

Lead design and production deployment of ML models focused on pricing, availability, forecasting, and optimization. Build data infrastructure, governance, testing/monitoring, and dashboards. Partner with executives and cross-functional teams, mentor others, and establish scalable data-science practices and experimentation frameworks.

Lead and grow a team of Conversation Designers to build and scale conversational AI experiences. Partner with Product, Engineering, Analytics, and ML teams to drive strategy, tooling, evaluation, and quality practices. Recruit and remove roadblocks, own strategic initiatives, and remain hands-on in designing, testing, and improving AI-driven conversational products.

Lead and scale teams building offensive and defensive AI agents and the ML, data, and safety systems that power them. Drive strategy, production-grade engineering, safety and governance, cross-team collaboration, and hiring/leadership development to deliver secure, reliable agentic security capabilities for customers.

Lead product marketing for PolyAI's voice assistant products: define messaging and positioning, drive go-to-market strategy and enablement, build competitive intelligence, develop personas and sales collateral, run customer and market research, support revenue enablement, scale and lead the product marketing team, and act as an external spokesperson.

Lead full sales cycle to drive CTV performance advertising growth in North America: prospect, close, launch and scale CTV budgets, manage key advertiser relationships, collaborate cross-functionally, represent Jampp at events (20% travel), and provide local feedback to improve global initiatives.

Lead development and deployment of cutting-edge ML models for pricing, design and analyze experiments, collaborate with product and engineering, present findings to stakeholders, and lead technical projects to influence team output and business metrics.