Top Senior Machine Learning Jobs in Orlando, FL

The Global Head of Solutions Engineering leads a team, ensuring technical excellence and customer success in pre-sales and onboarding while driving team development and cross-functional partnerships.

The Senior Scientist will design small molecules using computational tools, lead projects, manage external teams, and collaborate with machine learning and medicinal chemistry teams.

As a Principal Data Analyst, you'll leverage machine learning and AI to improve outcomes, manage large data sets, and guide analytics modelers for effective data solutions.

As the Engineering Lead, you will guide product strategy, manage and mentor engineers, and ensure successful execution in product areas, focusing on machine learning and technical expertise across teams.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

As the Director of Product Marketing for Databricks AI, you will lead the marketing strategy for AI products, collaborate with teams to create effective campaigns and product launches, and increase global outreach through partnerships.

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.

Lead development and maintenance of internal Python SDK frameworks and agentic workflows, build scalable FastAPI-based ML APIs, automate CI/CD with Jenkins and GitLab Runners, use Galileo for model evaluation and observability, and collaborate across teams to deliver production-grade autonomous systems.

As a Senior ML Engineer, you'll own ML-driven features from modeling to deployment, drive innovation in generative AI, and mentor junior members.

The Senior Vice President will lead projects focused on corporate performance, drive revenue growth, and develop business strategies while utilizing data modeling and machine learning techniques for analysis and solutions.

The Senior Machine Learning Engineer will deploy and maintain ML models, collaborate with cross-functional teams, and optimize ML system performance in a fully remote role.

Design, own, and scale end-to-end ML training and inference pipelines for on- and off-vehicle systems. Build extensible software across vehicle platforms, evaluate new models, grow training data scale, collaborate with ML and robotics engineers, and drive an E2E-first approach for deployment and field operations.

The role involves designing and prototyping advanced AI reasoning systems for real estate, focusing on LLM-powered applications while mentoring junior scientists.

Lead the design, development, and deployment of scalable machine learning and AI systems for enterprise clients, guiding architecture and mentoring engineers.

As a Staff AI Engineer, you will drive product-centric development of AI technologies, enhance evaluation systems, optimize reasoning strategies, and lead production-grade model tuning while balancing performance and cost.

The Cloud Inference Engineer is responsible for building and maintaining a scalable LLM inference platform, focusing on distributed systems and machine learning technologies while collaborating across teams to optimize performance.

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.

As VP of Engineering, you'll lead the application engineering strategy and team, integrating AI capabilities into products while ensuring quality and execution across backend, mobile, and desktop platforms.

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.

The Principal Machine Learning Engineer will design and scale ML systems for personalization and search, mentor engineers, and lead major ML initiatives at Fetch.

Lead design, development, and production deployment of scalable ML systems across domains. Own end-to-end ML lifecycle, architect pipelines and serving, drive MLOps maturity, mentor engineers, conduct design/code reviews, and ensure monitoring, governance, and model reliability in production.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.

The Staff Machine Learning Engineer will enhance Quora's recommendation systems, lead machine learning projects, and own end-to-end ML processes.

The role involves improving recommendation systems using machine learning, developing end-to-end ML systems, and collaborating with engineers.