Top Remote Machine Learning Jobs in Miami, FL

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own strategy and roadmap for Crunchbase's customer-facing AI data layer. Identify and validate model-derived data products, lead cross-functional development, set quality standards, drive adoption and monetization, and monitor performance and product economics.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Lead technical pre-sales for AI security solutions across SLED accounts. Responsibilities include technical discovery, architecture reviews, proof-of-concepts, product demonstrations, customer and partner training, deployment support, demo environment management, and post-sales handoffs. The role enables sales engineers and channel partners, engages technical decision-makers, and promotes secure deployment of agentic AI, including AI security best practices and integrations.

Support pre-sales execution for AI security solutions by conducting technical discovery, architecture reviews, demonstrations, proofs of concept, deployments, and training. Enable sales engineers and channel partners, manage demo environments, support customer handoffs, and build relationships with technical decision-makers. Promote secure AI and agentic AI deployment practices while helping identify, qualify, and close opportunities across existing and prospective customers.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Leads portfolio planning and cross-functional execution for Data Science Core and GenAI Studio programs. Establishes roadmaps, operating rhythms, priorities, dependencies, risk management, readiness criteria, decision processes, and success measures. Coordinates data science, engineering, product, research, privacy, legal, security, and business stakeholders from problem framing through deployment, adoption, and monitoring. Communicates technical tradeoffs and responsible AI considerations while improving team effectiveness, capacity planning, documentation, and delivery practices.

Create, solve, review, and validate coding-heavy machine learning tasks for AI training. Build and optimize models, training and inference workflows, data pipelines, evaluation systems, and reproducible Python workflows. Diagnose numerical and system-level failures, improve memory use and throughput, and verify technical correctness while working with coding agents.

Manage strategic state and local government accounts for NVIDIA’s AI and accelerated computing solutions. Own the full technology sales cycle, develop territory and account plans, build executive and technical relationships, collaborate with solution architects and channel partners, navigate public-sector procurement, forecast revenue, and achieve sales quotas. The role requires consultative selling to government organizations and travel of at least 25%.

Leads multifunctional initiatives defining safety architectures and requirements for autonomous vehicles. Develops safety concepts and analysis supporting continuous software delivery, improves safety metrics and analysis tools, evaluates safety data, and communicates readiness results. Collaborates with perception, AI, motion planning, and architecture experts to ensure DRIVE products meet rigorous safety standards.

Leads quantitative and qualitative market research on international development, AI adoption, institutional demand, funding, procurement, competition, and commercial opportunities. Evaluates AI and data service applications, develops market assessments and strategic recommendations, manages research initiatives, prepares executive presentations, and collaborates with leadership, technical, operational, and business development teams to support market entry and growth.

Own Fetch’s on-platform advertising measurement strategy, including event taxonomies, attribution, incrementality, reporting, and data pipeline standardization. Lead migration to standardized ad event infrastructure, define measurement methodologies such as multi-touch attribution and geo lift, and partner with engineering, data science, advertisers, and third-party measurement providers. Establish scalable measurement standards and ensure new ad products are instrumented and attributable from launch.

Lead AI/ML initiatives for Air Force condition-based maintenance, from predictive model development through production deployment. Architect data pipelines, develop machine learning, deep learning, NLP, and generative AI solutions, and build knowledge graph capabilities. Provide technical leadership, integrate models into applications and workflows, and monitor data quality, model performance, drift, and bias. Collaborate with engineering, cloud, software, and product teams while supporting defense aviation logistics and sustainment missions.

Develop AI agents, prompts, workflows, contextual data layers, orchestration frameworks, and machine learning models. Test and optimize solutions using structured and unstructured data, evaluate accuracy and scalability, analyze edge cases and failure modes, and document experiments and model performance. The 10-week remote internship is intended for students at least in their third year studying data science, AI, computer science, or a related field.

Manages global pharmaceutical quality systems, including eQMS implementation, maintenance, validation, enhancements, and lifecycle management. Optimizes quality workflows such as CAPA, change control, deviations, batch review, inspections, and audits. Develops quality metrics, reports, dashboards, and data governance practices while supporting digital transformation, automation, and AI initiatives. Partners with Quality, IT, analytics, regulatory, manufacturing, clinical, and other stakeholders on requirements, process improvement, system adoption, training, and change management.

Leads data science and advanced analytics initiatives for Auto Claims by developing machine learning and predictive modeling algorithms, integrating structured and unstructured data, and creating tools to support business decisions. Communicates modeling results to stakeholders, researches emerging techniques, manages moderately complex projects, and provides mentorship to junior data scientists. The role is remote with up to 10% travel to regional offices.

Own research and implementation of post-training methods for legal language models, including supervised fine-tuning, reinforcement learning, reward design, verifiers, preference modeling, evaluations, and distributed training. Lead experiments from research direction through production deployment, while debugging training instability, reward hacking, and divergence. Build rigorous evaluation systems and production-quality Python code for long-horizon legal reasoning and agentic workflows.

Build synthetic data pipelines, evaluation systems, benchmarks, verifiers, rubrics, and quality metrics for legal AI models and agentic workflows. Partner with researchers, legal experts, and customers to investigate model failures, validate metrics, maintain data quality and provenance, and convert expert feedback and product usage into training signals and improved evaluations.

Advise airport-industry customers on GIS solutions, demonstrate ArcGIS capabilities, and support account teams with technical sales strategies. Design solutions that align Esri technology with customer challenges, provide deployment and administration best practices, troubleshoot system architectures, and present at conferences. The role requires strong GIS, cloud, geodatabase, consulting, communication, and presentation skills, along with 25–50% domestic or international travel.

Leads enterprise Key Drivers Analytics and an Associate Director team delivering advanced analytics across pharmaceutical business priorities. Owns analytics roadmaps, methodologies, governance, modeling standards, talent deployment, and globally distributed delivery. Directs multivariate analyses, segmentation, diagnostics, scenario modeling, validation, insight generation, and executive recommendations. Partners cross-functionally to translate evidence into measurable business actions while ensuring reproducibility, compliance, responsible AI, and scalable analytical solutions.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Leads the enterprise Advanced Analytics and Modeling portfolio, strategy, roadmap, governance, investment priorities, and global operating model. Oversees analytics capabilities spanning precision health, commercial analytics, optimization, AI, NLP, GenAI, and unstructured intelligence. Partners with senior business and technology leaders to translate strategic decisions into validated, interpretable, reusable analytical solutions and measurable impact. Manages senior capability leaders and distributed US-Hyderabad teams while developing talent, allocating resources, and guiding scalable ModelOps and enterprise deployment.

Lead strategic sales of AI Workforce solutions, including Microsoft Copilot, AI agents, Viva, Windows 365, and Azure Virtual Desktop. Develop customer strategies, identify opportunities, build pipeline, conduct consultative business and technical conversations, and orchestrate internal teams and partners to close complex deals. The role requires expertise in technology sales, AI, forecasting, demand generation, stakeholder engagement, competitive positioning, and cross-selling across enterprise and regulated customers.

Lead analyst relations programs to improve Databricks’ positioning in industry evaluations, including Gartner, Forrester, and IDC. Develop differentiated narratives, submissions, demonstrations, customer evidence, and executive briefings. Scale analyst relations through AI-assisted workflows, convert analyst feedback into product and go-to-market recommendations, and influence product, marketing, sales, and executive teams. Manage multiple deadline-driven workstreams while improving analyst advocacy, market visibility, and evaluation outcomes.

The Director, AI Sales will grow Databricks’ enterprise AI business by driving strategic account adoption, production usage, bookings, and consumption. Responsibilities include developing AI sales plays, enabling field teams, securing executive and technical sponsorship, advancing complex opportunities, coordinating sales and partner stakeholders, and translating customer feedback into product and go-to-market recommendations.