Top Machine Learning Jobs in Miami, FL

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

Own the full machine learning lifecycle for search ranking and retrieval, including model training, deployment, serving, feature pipelines, evaluation frameworks, hybrid lexical-vector retrieval, large-scale embedding inference, query understanding, and permissions-aware multi-tenant search. Collaborate with infrastructure, AI, and backend teams to improve search relevance across ClickUp’s platform.

Leads the enterprise analytics organization, managing Analytics Engineers, Data Analysts, and BI Developers. Defines analytics strategy; delivers executive dashboards, KPI scorecards, operational reporting, semantic models, and self-service BI. Establishes data governance and metric standards, ensures data quality, partners with Engineering, Product, Finance, Operations, and executives, and translates business questions into actionable analytical solutions. Mentors analytics talent and drives prioritization, adoption, and measurable business outcomes.

Senior backend engineer responsible for setting technical direction, designing scalable distributed systems, building customer-facing web applications, mentoring engineers, and applying machine learning to large-scale healthcare data. The role requires Java, Scala, or Rust expertise, cloud systems experience, technical design leadership, cross-functional collaboration, and adoption of agentic engineering practices.

Leads Alkami’s enterprise and technology risk management program, including risk assessments, control evaluations, mitigation, monitoring, reporting, and escalation. Owns AI, machine learning, and generative AI governance, translating regulatory and risk expectations into practical policies, controls, and review processes. Partners with cross-functional risk owners and supports compliance initiatives involving business continuity, disaster recovery, regulatory management, and incidents. Reports to the Chief Compliance Officer in a fully remote role.

Provides product and technology legal counseling throughout the product lifecycle while operating Horizon3’s global privacy program. Advises Product, Engineering, Security, Compliance, and GTM teams on privacy laws, AI regulation, data flows, DPAs, cross-border transfers, privacy-by-design, incidents, audits, and customer diligence. Drafts playbooks, policies, notices, and contractual terms; supports enterprise negotiations; and delivers practical, risk-based guidance in a fast-moving cybersecurity environment.

Owns pricing and revenue optimization across a nationwide furnished-apartment portfolio. Develops dynamic pricing strategies, enhances machine learning models, analyzes elasticity and occupancy forecasts, builds performance dashboards, integrates external market data, and evaluates channel mix and ROAS tradeoffs. Partners with Marketing, Product, Engineering, and Operations while presenting pricing and investment recommendations to senior leadership.

Leads large-scale AI transformation programs for Cresta’s strategic enterprise customers. Serves as executive sponsor and trusted advisor to C-suite stakeholders, manages matrixed implementation and engineering teams, oversees complex deployments, standardizes delivery governance, and drives measurable customer value, adoption, expansion, and advocacy. Partners with Sales, Customer Success, Product, and Engineering while connecting technical outcomes to business ROI.

Adjudicate automated vessel detections humans cant resolve: identify dark/spoofed/low-confidence contacts, investigate AIS/GNSS manipulation and ownership, produce sourced identification records, and supply labeled ground truth to improve detection models.

Lead strategy and execution for enterprise and mid-market GTM across multi-unit restaurant brands. Drive C-suite engagements, modernize sales motions, scale AI-powered forecasting, partner with Product/Engineering, and represent Toast in industry forums to win large, complex contracts.

Provides strategic and hands-on biostatistical leadership across pharmaceutical discovery, translational, biomarker, and early research programs. Designs studies, analyzes complex biological datasets, develops advanced statistical methods and reproducible R workflows, and translates evidence into portfolio decisions. The role collaborates with quantitative and scientific functions, supports publications and external partnerships, mentors statisticians, and advances data-driven analytical practices.

Own product strategy, vision, roadmap, discovery, prioritization, prototyping, delivery, launch, and post-launch adoption. Conduct user and market research, use AI tools for synthesis and experimentation, collaborate with Design and Engineering, manage backlogs, define metrics, and communicate product direction across stakeholders.

Own the full enterprise sales cycle for Oversee’s leisure travel business, from prospecting through closing. Build relationships with OTAs, agencies, tour operators, and vacation providers; develop pipeline; identify target segments and use cases; refine positioning and sales strategy; lead complex stakeholder processes; and partner with Product and Engineering to convert market insights into a repeatable leisure sales motion.

Implement metadata governance frameworks for structured and unstructured data in cloud environments. Track data lineage and synchronize metadata across data catalogs, ESRI Kubernetes, and enterprise repositories. Use OpenLineage, Apache Atlas, and related tools to manage metadata and lineage. Enforce DoD metadata policies and NSG standards for geospatial datasets while advising clients and guiding data science teams.

Own AgentSee’s sales and go-to-market strategy as the first dedicated sales leader. Personally close early enterprise opportunities, refine the ideal customer profile, positioning, pricing, packaging, and sales process, and translate AI capabilities into measurable business value. Build repeatable sales operations and playbooks, provide market feedback to Product and Engineering, and eventually hire and lead the AgentSee sales organization.

Leads enterprise cybersecurity architecture for AI, cloud, hybrid, and on-premises environments. Designs secure AI architectures, cloud foundational controls, zero-trust identity models, API and data protections, and secure LLM, RAG, agent, and MCP integrations. Establishes governance, reusable security patterns, model-usage procedures, compliance controls, and audit readiness across AWS and Azure. Advises executives and technical teams, mentors security professionals, and drives secure cloud migrations while addressing AI/ML risks such as adversarial attacks, model poisoning, data drift, bias, and data leakage.

Own enterprise data inventory and translate business needs into data models, quality rules, mappings, and acceptance criteria. Partner with data and software teams on pipelines, governance, monitoring, and lifecycle management. Prepare data for agentic workflows, including semantic layers, knowledge bases, retrieval indexes, and evaluation datasets. Develop reusable analytical models, reports, dashboards, and decision-support products while monitoring data quality and communicating limitations and business impact.

Conducts research using crewed and uncrewed tropical cyclone reconnaissance data to improve hurricane analysis and forecasting. Develops and evaluates machine learning methods for estimating tropical cyclone surface winds, creates real-time products for National Hurricane Center testing, runs and verifies HAFS forecasts, manages and visualizes complex data, uses high-performance computing, publishes findings, and presents results at conferences.

Lead a global product team building automation-first, AI-assisted investigation and agent-facing tooling for AML, KYC, EDD, and sanctions screening. Define roadmap, metrics, vendor strategy, and regulatory controls to improve investigation quality, cycle time, and operational efficiency while ensuring security, privacy, and auditability.

Conducts advanced statistical genetics and bioinformatics research on Alzheimer’s disease, related dementias, and Alpha-1 Antitrypsin deficiency. Designs reproducible analyses of genome-wide association, sequencing, genomic, and clinical data using R and Python. Develops machine learning and large language model approaches for disease prediction and risk stratification. Publishes research, contributes to grants, collaborates with principal investigators, supervises trainees, and advances computational genomics methods.

As a Machine Learning Engineer, you will enhance internal libraries for deep learning, collaborate with researchers, and optimize workflows for cost savings.

Partner with healthcare clients to discover, design, and deliver production-grade AI/LLM solutions. Architect cloud-native systems, build and deploy ML/LLM applications, prototype rapidly, troubleshoot distributed systems, and lead client engagements to drive measurable business outcomes while collaborating across product, platform, and engineering teams.

Lead B2B activation marketing to drive patient starts from commercial referral channels by building scalable systems, attribution frameworks, and repeatable playbooks. Implement MarTech and data-driven strategies, run A/B and incrementality tests, automate campaign execution using AI/ML and LLM tools, and templatize activation campaigns while managing and growing a cross-functional team.

Lead technical project success for enterprise AI infrastructure engagements. Collaborate with engineers, clients, and account leaders to capture requirements, decisions, dependencies, risks, and tradeoffs. Track constraints involving security, compliance, data sovereignty, procurement, and restricted environments. Maintain project visibility, align deliverables with business objectives, resolve issues, support implementation-to-operations handoffs, and identify expansion and renewal opportunities. Translate complex technical concepts for engineering, business, and executive stakeholders.

Analyze business processes, data quality, and datasets to identify AI and automation opportunities. Translate business requirements into AI/ML use cases, collaborate on model development, evaluate model performance, and deliver dashboards and reports. The role also supports data validation, AI solution monitoring, emerging technology research, governance, compliance, responsible AI, prompt engineering, and generative AI initiatives while partnering with business, data science, engineering, and product teams.