Top Senior Machine Learning Jobs in Orlando, FL

Lead a team to develop groundbreaking technology combining NLP, big data, and AI to enhance digital communication and interaction.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

Lead the Client Solutions team, ensuring the execution of complex transactions while driving innovation and client advocacy. Oversee operations, build client relationships, and implement strategic frameworks for growth.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.

The Forward Deployed Engineer collaborates with clients to solve complex problems using technology, integrating systems, writing production code, and leading projects to deliver impactful solutions in areas like financial crime prevention and national security.

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

As a Sr Director Analyst, you will create actionable research in analytics and AI, advise clients, and lead a team in impactful research. Responsibilities include engaging clients, presenting insights, and mentoring team members in analytics & AI best practices.

As a Principal Data Scientist, you'll design and deploy cutting-edge machine learning models to drive financial success for customers and guide technical teams.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

The Senior Product Manager will lead the integration of machine learning into search relevance, defining product vision and collaborating with teams to enhance ecommerce search functionality.

Serve as the primary technical resource for channel partners to enable partner sales through training, demos, PoV engagements, joint account strategy, and creation of repeatable technical assets and reference architectures. Influence product roadmap via partner feedback and represent 7AI at events to scale partner-led pipeline and long-term customer success.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Manage a portfolio of B2B SaaS customers as their primary contact to drive adoption, onboarding, migrations, engagement, and renewals. Deliver training, business reviews, issue resolution, and strategic expansion plans. Coordinate cross-functionally with sales, product, and support while reporting on customer health, usage metrics, and opportunities for upsell.

Lead the Data Sources product roadmap for document parsing, fraud detection, and bank aggregation. Drive metrics (parse accuracy, fraud catch rate, connection success, SLAs), write specs, engage clients, mentor PMs/engineers, and represent the platform externally. Prioritize document types, extraction models, reliability, and scalability to improve conversion, client satisfaction, and operational efficiency across mortgage, tenant screening, and government use cases.

Lead product strategy and roadmap for two flagship B2B SaaS solutions in Food Equipment Services. Drive discovery, prioritize AI-driven quoting and design features, partner with engineering and GTM teams, define success metrics, and oversee delivery, adoption, and continuous improvement.

Serve as technical lead in pre-sales for identity verification and fraud prevention. Lead discovery, workshops, POCs, demos, and solution design; advise on risk/compliance; align cross-functionally; influence product; mentor junior consultants and contribute thought leadership.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Lead technical pre-sales and enterprise rollouts by owning infrastructure strategy, PoCs, migrations (on‑prem to cloud), DMS/CRM integrations, InfoSec discussions, and stakeholder engagement with C-level sponsors to enable scalable deployments and upsell opportunities.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Senior Product Manager will lead product initiatives, manage the product lifecycle, and ensure solutions meet customer needs while driving market growth and achieving KPIs.

The Senior Backend Data Engineer will extend data ingestion and processing pipelines, build APIs and backend services, and provide technical leadership.

Lead data quality and data management for oncology studies, overseeing DM teams, vendor/CRO management, and compliance with CDISC/ICH-GCP. Develop risk management, integrate and surveil multi-source data, advise stakeholders on data collection and standards, produce metrics and dashboards, manage project resourcing and finances, review contracts, and deliver training to ensure high-quality, regulatory-compliant clinical and real-world data.

Lead strategic relationships with enterprise healthcare accounts to drive adoption, retention, and expansion of Nabla's AI clinical assistant. Oversee onboarding, monitor account health, translate customer feedback to product, collaborate with sales and product teams, and perform periodic on-site executive engagement and adoption initiatives.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.