Top Machine Learning Jobs in Tallahassee, FL

Coordinates strategic AI programs across engineering, product, legal, risk, compliance, security, HR, and business teams. Develops execution plans, governance frameworks, status reporting, risk registers, and executive communications. Supports AI platform and agent deployment initiatives, AI policy development, enterprise training, stakeholder alignment, and adoption. Requires strong program management, AI technology understanding, organizational skills, and experience managing complex cross-functional initiatives.

Build and own production-grade generative AI applications for legal technology, specializing in RAG, agentic systems, advanced search, embeddings, reranking, evaluation, and LLM workflows. Responsibilities include architecting modular Python applications, refactoring legacy code, implementing testing and observability, optimizing performance and costs, ensuring resilience and security, reviewing code, and supporting deployments and incident resolution.

Leads the scientific direction and technical roadmap for a permanent magnet research vertical. Responsibilities include guiding computational materials discovery and AI modeling, developing manufacturable magnet formulations, building and mentoring multidisciplinary teams, managing intellectual property, coordinating national laboratory and industry partnerships, and connecting simulation with experimental validation. The role also supports commercial licensing, external scientific communications, publications, and federally funded research programs.

Build production-ready agentic AI capabilities focused on monitoring, guardrails, evaluation, security, quality, and human-agent collaboration. Perform machine learning tasks including exploratory data analysis, feature engineering, and model fine-tuning. Translate research into scalable software, rapidly prototype features, collaborate cross-functionally, and explore emerging agentic technologies.

Own the strategy, roadmap, and success metrics for AI security capabilities across the Pathfinder platform. Serve as the internal expert on agentic AI threats, identity security, and emerging attack techniques. Define requirements for securing AI agents, MCP servers, and orchestration frameworks; conduct market and competitive research; lead design partner programs; coordinate cross-portfolio product work; and support analyst, customer, marketing, and pre-sales engagements.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Manages backlogs, roadmaps, prioritization, requirements, user stories, release planning, and product metrics. Partners with stakeholders, Engineering, AI, UX, Data Science, and Architecture teams to deliver enterprise AI-enabled products aligned with governance, Responsible AI, and business objectives.

Leads product strategy, roadmap, pricing, security product direction, AI governance, integrations, regulatory capabilities, customer discovery, launches, and product team development. Partners with Engineering, Research, Sales, Marketing, Finance, and executives to improve retention, expansion, win rate, margin, and enterprise adoption. Owns detection quality, deployment models, secure-by-design requirements, compliance certifications, competitive positioning, and board-level product communications.

Own and improve ClickUp’s voice AI systems, including real-time speech-to-text, audio processing, context-aware transcription, LLM post-processing, mention resolution, formatting, and voice-to-action workflows. Evaluate and integrate ASR models for accuracy, latency, and cost, while collaborating across product and platform teams to deliver voice and multimodal assistant features across desktop, mobile, web, and browser extension products.

Leads enterprise CrowdStrike deployments, architecture, compromise assessments, threat hunting, SOC modernization, detection engineering, cyber analytics, Purple Team exercises, and incident response. Advises CISOs and executives, manages cross-functional teams, designs global 24/7 SOCs, and coordinates breach containment and recovery. Requires deep CrowdStrike expertise, cybersecurity leadership, scripting, network and detection engineering, and executive communication skills.

Leads AI governance and assurance engagements, designing policies, controls, operating models, risk assessments, and compliance programs. Evaluates AI security, model governance, third-party solutions, and control effectiveness against frameworks including NIST AI RMF, ISO 42001, and the EU AI Act. Collaborates with security and engineering teams to test threats such as prompt injection, model manipulation, data poisoning, and leakage. Advises executives and clients, develops methodologies and proposals, researches emerging AI risks and regulations, and supports business development.

Review and annotate robotic-system video footage by identifying objects, movements, events, visual features, and anomalies. Provide feedback to improve video datasets and annotation consistency, collaborate with AI teams on annotation protocols, document observations, participate in quality reviews, and recommend improvements to video capture and labeling strategies.

Designs, builds, and operates observability and SRE systems that improve IT service visibility, reliability, performance, and resilience. Responsibilities include metrics collection, monitoring, alerting, APM, RUM, synthetic transactions, SLOs, incident response, capacity planning, infrastructure automation, self-healing systems, and production readiness reviews. The role also applies AI-enabled operations, supports on-call rotations, reduces operational toil, and partners with development teams on architecture and chaos testing.

Leads Helium 10’s global product management function across the United States and China. Owns multi-quarter roadmaps, new-product discovery and delivery, direct-to-consumer and omnichannel expansion, AI-native product development, customer discovery, commercialization, analytics, and cross-functional execution. Manages and develops product managers, establishes operating standards, ensures timely high-quality releases, and communicates business outcomes to executive stakeholders.

Drive new business revenue across the Western Territory by selling complex healthcare technology and services, including AI-enabled EHR and revenue cycle management solutions. Manage the complete enterprise sales cycle from prospecting, discovery, demonstrations, proposals, negotiations, and closing through accurate forecasting and CRM updates. Build relationships with healthcare decision-makers, manage RFPs, develop territory plans, and travel 50–75% of the time.

Build and lead North’s Applied AI engineering team, taking AI solutions from prototype to production in regulated financial-services workflows. Responsibilities include architecting agentic systems, chatbots, copilots, and ML models; establishing secure enterprise integrations; managing evaluations, monitoring, CI/CD, incident response, and cost controls; and setting technical strategy and responsible-AI governance. The role requires close collaboration with business, product, risk, compliance, legal, and security stakeholders.

Own cloud security across AWS and Azure, including identity, network, application, container, data, and AI security. Build policy and infrastructure controls as code, integrate security into CI/CD, protect regulated health data, and manage detection, incident response, vulnerability remediation, and compliance. The role also develops AI security guardrails and coaches engineering teams while operating production security controls and supporting on-call responsibilities.

Leads enterprise AI solution strategy, architecture, pre-sales, and implementation delivery for customers across the Americas. Defines AI use cases, validates feasibility, designs scalable architectures, guides Professional Services teams, and resolves complex technical challenges. Develops AI service offerings, methodologies, reusable assets, and enablement programs while mentoring architects, consultants, and project leaders. Requires deep experience with enterprise transformations, LLMs, multi-agent systems, generative AI, data architecture, cloud platforms, and production AI deployments.

Own enterprise technical deployment roadmaps, milestones, acceptance criteria, governance, and post-launch adoption. Coordinate Product, Engineering, Delivery, Support, and Sales teams to resolve blockers, manage resources, map workflows, track KPIs, and demonstrate ROI. Partner with account executives on technical expansion opportunities and establish scalable deployment playbooks, PMO templates, and integration patterns.

Leads AI governance, risk assessment, security, privacy, and compliance programs for generative and agentic AI systems. Coordinates cross-functional teams, reviews customer and regulatory requirements, establishes AI agent management structures, automates governance controls, manages technical improvement projects, supports audits, delivers training, and reports risks and metrics to senior leadership. The role requires extensive cybersecurity experience, AI security and threat modeling expertise, framework compliance, project management, and executive communication.

Own the vision, strategy, and roadmap for Root’s pricing platform and machine learning infrastructure. Lead engineering and partner with data science, actuarial, and engineering teams to improve pricing workflows, model development, deployment, monitoring, and regulatory operations. Drive self-service tooling, LLM-enabled data science workflows, platform reliability, and nationwide expansion while translating business needs into product requirements and prioritized investments.

Own technical evaluations, deployments, and production integrations for major government and enterprise customers. Build Python, SQL, agents, tools, and REST integrations within customer environments; lead proofs of concept, deployments, executive briefings, and technical account relationships. Triage bespoke versus reusable capabilities, influence the product roadmap, and review other engineers’ work. The role requires strong cloud, containerization, data, communication, and ambiguous problem-solving skills.

Design and develop scalable backend systems using Kotlin, Micronaut, and Spring. Build RESTful APIs, optimize PostgreSQL and Elasticsearch databases, implement RabbitMQ-based asynchronous processing, integrate AI tools, and create automated tests. Deploy and monitor services on GCP using Docker, Kubernetes, and Terraform. Collaborate cross-functionally, participate in code reviews, troubleshoot performance issues, and deliver reliable backend products.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

Design and deploy production-ready LLM pipelines and agentic workflows, automate large-scale multimodal dataset pipelines, monitor and improve agent performance, and integrate AI agents with 3D scene composition. The role also involves process documentation, incident response, and continuous improvement, with collaboration across the engine team and company founders.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.