Top Machine Learning Jobs in Orlando, FL

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

Support risk and analytics efforts by performing SQL/Python-based analysis, monitoring portfolio health, building scalable reports, collaborating cross-functionally, and integrating AI tools to surface insights that inform product, risk, and growth decisions.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.

Lead development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

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.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

Lead the global engineering strategy for BNY's Fraud Hub, overseeing platforms for fraud detection and prevention, leveraging AI for enhanced security and operational excellence.

Design, train, and productionize machine learning models for fraud and identity risk across the full ML lifecycle. Research new fraud types, perform feature engineering and labeling, write production-ready code for real-time decisioning, monitor models, and provide analyses to inform product, sales, and data acquisition.

Postdoctoral researcher in computational and theoretical materials science performing first-principles (DFT) calculations and developing machine-learning methods to design materials for quantum and energy applications, predict synthesizability, and study defect physics; collaborate, communicate results, and work independently on cutting-edge materials informatics research.

Lead global 24/7 security operations and the full incident response lifecycle. Direct cyber threat intelligence and convert it into detection coverage and defensive architecture. Establish detection-as-code and continuous validation practices, coordinate cross-functional incident response, integrate automation/ML, and build a diverse, distributed team focused on adversary-focused detection and rapid, measured defensive actions.

Oversee global analytics and algorithm design initiatives for a nonprofit: identify high-impact projects, coordinate with student directors, collect feedback, design and run training for developers and technical advisors, and form partnerships to support implementation. Volunteer commitment ~5-6 hours/week.

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

Design and build reinforcement-learning training environments and diverse tasks to evaluate and improve LLM agents; iterate rapidly on task designs from customer feedback, deliver high-quality outputs with minimal supervision, and maintain PST overlap for collaboration.

Lead and scale a strategic sales channel for an LTL logistics company, building high-performance sales teams, aligning commercial strategy with operations, driving growth through CRM and Power BI analytics, and executing aggressive performance and travel-heavy sales plans.

Lead the commercial engine: build partnership function, close enterprise platform partnerships, own full marketing (positioning, content, paid, website), design AI-leveraged GTM stack, translate product-market fit, run pipeline and commercial reporting, and hire a team when metrics justify growth.

Lead enterprise design and deployment of standardized, scalable bovine IVF production systems. Drive process architecture, SPC, automation, AI/advanced analytics, Lean/Six Sigma, quality systems, and organizational development to reduce variability, increase throughput, and ensure consistent outcomes across laboratories and field operations.

Lead and execute product strategy for Everyday Money: define product thesis and roadmap, ship product lines, run AI innovation lab for agentic consumer experiences, manage and develop PMs, partner with design, Credit, and external partners, and own business economics and compliance for durable retention and monetization.

The Staff Product Manager will define product strategy, lead the product lifecycle, collaborate across teams, and drive innovation in claims processing software.