Top Senior Machine Learning Jobs in Miami, FL

Design, optimize, and scale ClickUp's search infrastructure using OpenSearch/ElasticSearch. Improve relevance, speed, and real-time indexing; build vector/semantic search capabilities; create measurement frameworks; integrate search with AI and product features; troubleshoot at scale; and mentor junior engineers to maintain high search quality under heavy load.

Design, scale, and optimize ClickUp's search infrastructure using OpenSearch/Elasticsearch. Improve relevance, speed, and real-time indexing, build vector search capabilities, create evaluation frameworks, and collaborate with AI/backend/product teams to integrate and troubleshoot search at scale.

The Senior Backend Data Engineer will extend data ingestion and processing pipelines, build APIs and backend services, and provide technical leadership.

Lead Tekmetric's API product strategy and roadmap for the SaaS platform. Own API lifecycle (contracts, versioning, documentation), drive developer experience and adoption, identify integration opportunities, lead generative AI initiatives, perform user research and analytics-driven prioritization, collaborate across design/engineering/sales, train internal teams, and measure business impact.

Designs, develops, and deploys end-to-end AI/ML solutions for financial services, including generative AI applications, LLMs, RAG systems, data pipelines, and production machine learning models. Builds AWS-based infrastructure and ETL workflows, performs model validation and risk assessments, establishes benchmarking and monitoring frameworks, and ensures compliance with banking regulations, privacy requirements, and ethical standards. Collaborates with technical and business stakeholders to identify AI opportunities and communicate complex concepts.

Lead planning, execution, and optimization of cross-functional hardware and software projects for robot development, manufacturing, testing, upgrades, and deployments. Coordinate mechanical, electrical, embedded, systems, manufacturing, and operations teams, define scope and timelines, mitigate risks, implement process improvements, run sprints, and maintain project documentation and stakeholder communication.

Lead Woolpert's partner marketing for the Google relationship: develop and execute joint go-to-market plans, run integrated campaigns, enable sales, create partner collateral, measure KPIs, and coach one specialist to drive co-selling and pipeline growth for Digital Innovations.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Lead and grow a global engineering team building endpoint visibility, prevention, and on-device ML across Windows, macOS, and Linux. Own roadmap and delivery, direct model development and telemetry, drive cross-platform protection parity, coordinate with product and partner teams, and represent the team externally through research and conferences.

Build and operate a secure Kubernetes-based AI/ML platform for government test and evaluation teams. Responsibilities include GPU scheduling, workload orchestration, infrastructure-as-code, GitOps, observability, capacity planning, upgrades, security hardening, compliance support, and operational documentation. The role involves restricted and disconnected environments, automated security tooling, collaboration with government and engineering stakeholders, technical leadership, and mentoring.

Lead statistical design and analysis for Phase I-IV clinical studies, develop protocols and SAPs, perform efficacy and exploratory analyses, run simulations, apply advanced methods (mixed models, longitudinal), oversee datasets (ADaM/CDISC), use R and SAS for analyses, and provide strategic statistical guidance to cross-functional teams supporting regulatory submissions.

Lead and grow a team of 5-7 enterprise sales reps in the Bay Area, recruit and develop sales leaders, build business plans, drive new-logo acquisition and account expansion, manage the sales cycle from lead generation to close, develop GTM strategy, and report to the VP of Sales. Role supports ambitious quarterly and annual goals and may require occasional work outside standard hours.

Lead the vision and execution of data product roadmap; translate business needs into epics and acceptance criteria; partner with data engineering and analytics; run agile ceremonies and manage backlog; champion data-as-a-product; scope and pilot AI/ML capabilities; present roadmaps and business cases to leadership.

Sell Fiddler’s AI observability platform to enterprise customers: prospect, navigate complex multi-stakeholder deals, demonstrate technical and business value for ML/AI solutions, close revenue, grow accounts, and collaborate cross-functionally. Travel as needed (10–25%).

Full-cycle territory sales role selling Greenway Health's EHR, RCM, and AI-driven healthcare solutions. Responsibilities include prospecting, lead generation, demos, RFP management, proposal configuration, negotiation, closing, maintaining Salesforce, meeting quota, and providing market feedback. Role requires heavy travel (50–75%) and collaboration with internal solutions consultants to deliver value-based technology and revenue cycle capabilities to ambulatory healthcare clients.

Conduct research and develop identity and probabilistic-matching models for Netflix's ad-supported tier. Apply ML and statistical methods, ensure privacy-preserving solutions (differential privacy, anonymization), prototype and deploy production models, deliver datasets and tools, and partner with product, engineering, and business stakeholders to measure and drive impact.

Lead a Demand Planning Center of Excellence to standardize processes, improve forecast accuracy, automate planning, and support S&OP. Mentor brand demand planners, drive cross-functional collaboration, implement planning tools (statistical/AI/ML), establish KPIs/reporting, and enable scenario planning to optimize spare-parts availability and inventory efficiency.

Lead and build a Demand Planning Center of Excellence to improve forecasting accuracy, standardize processes, automate planning, and support S&OP. Manage and mentor brand demand planners, partner cross-functionally (Supply Chain, Finance, IT, Asset Management), drive continuous improvement, reporting, scenario modeling, and enable data-driven decisions for spare parts and inventory optimization.

Lead a Demand Planning Center of Excellence to standardize processes, improve forecast accuracy, enable S&OP, mentor brand demand planners, automate planning workflows, resolve data quality issues, and collaborate cross-functionally to optimize spare-parts availability and inventory performance.

Lead credit analytics for the Send Now Pay Later product: build and own valuation and vintage models, manage credit policies, monitor portfolio health and NPL trends, integrate ML scorecards, and evaluate alternative data to optimize approvals and loss performance.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, valuation and NPV models, vintage analysis, executive reporting, model integration and testing, and alternative data integration to optimize approval rates and portfolio health.

Lead credit analytics for the Send Now Pay Later product: build and maintain credit policies, valuation and NPV models, vintage analysis, portfolio surveillance, executive reporting, model integration/testing, and alternative data exploration to optimize approval rates and manage portfolio risk.

Design, build, and operate core AI capabilities and reusable model integrations for an enterprise platform. Integrate foundation models into production, optimize performance and reliability, prototype new techniques, and support scalable backend services and distributed AI systems in collaboration with cross-functional teams.

Lead and scale end-to-end data annotation operations: set quality standards, build and manage an in-house annotation team and vendors, translate research into annotation guidelines, implement QA systems, drive AI-assisted labeling, partner with ML/CV and product, and own metrics and reporting.

Own end-to-end product development for AI/ML revenue cycle solutions: define vision and roadmap, write specs and user stories, prioritize backlog, work closely with data scientists and engineers, drive agile delivery, ensure quality, and measure product performance with stakeholders.