Top Machine Learning Jobs in Miami, FL

Lead and architect high-value healthcare analytics engagements, build reusable analytic frameworks (DBT), partner with product and engineering, mentor analysts, ensure analytic quality, and represent Arcadia externally to drive population health and value-based care outcomes.

Lead the end-to-end demand-to-value pipeline for enterprise AI: identify high-impact use cases, make buy/build decisions, drive adoption, establish baselines and ROI, and build a team to scale business-facing AI delivery while providing credible technical evaluation of ML and generative AI.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Intern will own and deliver a scoped engineering project on Deepgram's voice platform (ASR/TTS/LLM/API/SDK), ship reviewed code to staging/production, use AI in development workflows, improve a component measurably, and present results with documentation.

The Director of Product Management for ML Platform will own the product strategy and execution, mentor PMs, and collaborate with ML teams to enhance infrastructure and manage costs.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead planning, deployment, tuning, and operational support of CrowdStrike Falcon's AI/ML detection and response capabilities. Implement and troubleshoot AI-driven detection models, automation playbooks, API integrations, and threat-hunting for customers. Provide training, mentorship, and customer-facing collateral while optimizing detection efficacy and integrating Falcon into customers' security workflows.

Analyze malware and customer detection reports to improve machine-learning based detections, reduce false positives, reverse engineer binaries, review product detections, and support internal teams on threat detection efficacy and remediation.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

Senior CAO Elite Analyst II performs advanced threat hunting, dark web and intelligence research, delivers customer briefings, responds to ad-hoc intel requests, validates security controls using MITRE ATT&CK, and partners across teams to protect and advise enterprise customers.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead the design and implementation of critical Safety AI initiatives, focusing on real-time perception systems for edge devices and optimizing models for production deployment in safety-critical environments.

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.

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.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

Lead the B2B Managed Lifecycle Marketing team to own end-to-end lifecycle strategy for managed enterprise accounts. Drive pipeline, onboarding, retention, and expansion through integrated email and in-product campaigns, analytics, experimentation, and cross-functional collaboration while managing a team of three.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

The Staff Product Manager, Conversion ML will shape product strategy for Liftoff's machine learning system, Cortex, develop new ideas, conduct experiments, and adapt roadmap based on data.

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

Design and implement analytics and MLOps solutions for healthcare payers on Databricks, mentor junior staff, build CI/CD and provisioning patterns, and collaborate with data scientists to deliver scalable analytics platforms.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

Lead negotiation and closing of SaaS, cloud and AI-related commercial agreements; partner with sales, product, engineering and support; ensure data privacy, security, and evolving AI governance compliance; enable sales through training and high-volume deal support; find commercial solutions to close complex, time-sensitive deals.