Top Machine Learning Jobs in Tallahassee, FL

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

This role involves designing, deploying, and maintaining machine learning and AI models in production, managing ML pipelines, and ensuring system reliability and performance.

The AI Developer is responsible for designing and deploying AI solutions, including autonomous agents and predictive models, and integrating them into business operations.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

AVIA seeks experts in Digital Health and AI for advisory roles to support healthcare systems' technological transformations as part-time, project-based consultants.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

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.

Lead cross-functional strategic projects, build quantitative models and dashboards to track KPIs, align technical and commercial teams, audit and design scalable operational workflows, and synthesize technical and financial data into leadership-level presentations.

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.

Design, build, and deploy K-12 AI features (lesson planning, grading, tutoring, admin analytics) while ensuring FERPA/COPPA compliance and child-safety guardrails. Measure impact, iterate with curriculum and legal partners, and maintain production-grade documentation, testing, and runbooks for deployed AI systems.

Lead development and productionization of large-scale ranking and personalization ML systems. Build data pipelines, features, and models (batch and real-time), collaborate cross-functionally, run experiments, and improve infrastructure for search, recommendation, and marketplace optimization.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.

The Senior Machine Learning Engineer will build and own production ML systems, manage end-to-end workflow, debug issues, and mentor others.

Lead and scale full-stack engineering teams for Yahoo Mail; define engineering vision and roadmap; drive AI-native development and AI transformation using Generative AI/LLMs and agents; partner with Product, Design, and Data Science to deliver scalable cloud-native mobile and web experiences; hire, mentor, and retain engineering talent while guiding architecture, technical reviews, and platform modernization.

Design, build, test, deploy, and maintain production AI capabilities (agents, workflows, models, MCP servers, APIs) across a SaaS dental platform. Train and operate ML models, implement RAG and vector DB solutions, use AI-assisted tools, collaborate in design and code reviews, and support production reliability and monitoring.

Design, optimize, and operate production LLM inference and training pipelines. Improve latency, throughput, and GPU utilization using techniques like batching, quantization, FlashAttention, and kernel-level profiling. Deploy and autoscale multiple models on shared GKE GPU clusters, consult with clients on performance and cost requirements, and carry prototypes to robust, scalable production services.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The Senior Product Architect will design security products, collaborating with product management and engineering teams, focusing on architecture and functionality for high-level product features.

Design, develop, and deploy end-to-end AI/ML applications (RAG, chatbots, agentic workflows). Build scalable data pipelines, apply graph analytics, entity resolution, and NLP for risk scoring, anomaly detection, and investigative prioritization. Develop models, REST APIs, and deploy/manage solutions in AWS to support federal mission use cases.

Build and re-architect Shipt's LLM-native search stack including retrieval and ranking systems. Design multi-task and multi-objective models, integrate personalization signals, develop hybrid dense/sparse retrieval, and apply generative retrieval and query expansion. Analyze search data, report findings to leadership, and partner with senior scientists and ML engineers to improve relevance, revenue trade-offs, and operational metrics.

Develop and scale reinforcement-learning systems that close the loop between automated labs and reward models. Build synthetic data engines and inference infrastructure for large-scale training, maintain evaluations of learned policies using proprietary experimental datasets, and address real-world challenges like experimental noise and expensive queries.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

As a Senior Staff Machine Learning Engineer, you will lead the development and deployment of machine learning models, ensuring they drive business growth and meet performance requirements. You will collaborate with teams, manage data pipelines, and implement state-of-the-art solutions while continuously improving model performance.

The role involves developing and deploying machine learning models for forecasting within the Camus platform, requiring collaboration and technical depth in ML.