Top Senior Machine Learning Jobs in Orlando, FL

Leads end-to-end customer onboarding and implementation programs, translating customer goals into project plans, milestones, dependencies, risks, and success metrics. Coordinates Sales, Product, Engineering, Support, Customer Success, trainers, and subject-matter experts without performing hands-on technical implementation or training. Establishes scalable operational frameworks, manages cross-functional accountability, oversees technical readiness, tracks adoption, facilitates stakeholder communications, and ensures customers are prepared for go-live.

Own the strategy and roadmap for Constructor’s search quality and Product Discovery Engine. Drive measurable improvements in relevance, conversion, revenue per visit, and GMV across retail verticals. Partner with ML, data science, and engineering teams to productionize state-of-the-art retrieval, ranking, query understanding, personalization, and LLM capabilities. Establish evaluation frameworks, investigate quality issues, align multiple teams, and expand into chapter-wide product leadership.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

Own lifecycle marketing performance across patient onboarding, activation, early care, and retention. Design and analyze multichannel experiments, build reporting and dashboards, write SQL, diagnose funnel and segment performance, and integrate AI and machine learning signals into lifecycle journeys. Collaborate with Product, Operations, Data Engineering, Marketing Operations, Analytics, and Creative to improve patient outcomes and measurable business performance.

Lead the roadmap and delivery of an AI-native L1 IT operations agent. Partner with customers, design partners, engineering, and go-to-market teams to ship enterprise-scale capabilities, improve self-service adoption, and build trust through transparent agent experiences and feedback loops. Drive product strategy from discovery through launch in a fast-paced, ambiguous environment.

Designs and leads scalable contact center architectures using Zendesk, Amazon Connect, and AWS. Defines modernization strategies, oversees integrations, governance, security, and compliance, and mentors presales specialists. Supports discovery, solution design, demonstrations, proofs of concept, presentations, and technical documentation. Collaborates with business leaders, IT teams, vendors, and partners while driving innovation in omnichannel, AI-enabled customer service technologies.

Lead enterprise AWS consulting engagements from architecture through deployment. Design resilient cloud-native, serverless, and containerized solutions; migrate legacy infrastructure; and deliver Generative AI and machine learning workloads using AWS services. Partner with executive stakeholders, build proofs of concept, drive cloud adoption and account growth, mentor engineers and architects, and develop reusable Terraform modules, Well-Architected Review frameworks, and delivery best practices.

Leads the AI product strategy and roadmap, extending governed Alteryx workflows and business logic into enterprise AI agents and LLM ecosystems. Owns the Faster, Better, Cheaper ROI narrative, benchmarks product performance, quantifies customer value, champions trustworthy AI through the VURA framework, and represents the product vision with customers, analysts, and external audiences.

Leads Dandelion Health’s AI developer business by building pipeline, closing clinical AI data and validation partnerships, recruiting developers into its marketplace, and achieving revenue targets. Develops commercial strategy, manages executive relationships, structures agreements, and collaborates with marketing, product, data, engineering, and clinical informatics teams. Represents the company at industry events and advises on clinical AI validation, regulatory, payer, and competitive dynamics.

Researches, develops, tests, and maintains materials-aware machine learning models and software. Designs scalable ML systems, improves model interpretability and uncertainty quantification, and develops inverse-design capabilities. Collaborates with product, engineering, and external research teams to deliver customer-focused AI solutions, publishes research, reviews code, analyzes model performance, and mentors developers.

Develop and deploy machine learning algorithms that improve real-time device identification and fraud detection. Own data science projects from experimentation through production, including supervised, semi-supervised, and unsupervised learning, real-time inference, training automation, exploratory analysis, and model-to-service integration. Contribute to engineering best practices, collaborate within a global remote team, and participate in a shared on-call rotation.

Improve 1Password’s technical SEO across consumer, PLG, and enterprise websites. Responsibilities include diagnosing and resolving crawlability, indexing, rendering, performance, structured data, internal linking, and international SEO issues; implementing CMS changes; partnering with engineering on requirements and release QA; leading migration workstreams; and building monitoring, dashboards, automation, and repeatable processes using search, analytics, crawl, log, and CMS data.

Own product strategy and delivery for agentic document management, policy and procedure workflows, and compliance gap assessments. Partner with customers, design, engineering, and go-to-market teams to build reliable, explainable AI experiences that accelerate audit readiness and security program expansion. Responsibilities include defining product requirements, evaluating AI outputs, improving quality, synthesizing customer feedback, prioritizing roadmaps, and shaping product culture.

Own the vision, strategy, roadmap, discovery, delivery, and continuous improvement of Rezilient’s member experience products. Partner with clinical operations, engineering, design, customer success, and sales to ship accessible, engaging healthcare experiences. Define requirements, prioritize backlogs, establish product metrics, ensure healthcare compliance, and help integrate AI into care delivery. The role requires experience scaling consumer health products, building AI or machine learning features, and operating effectively in a regulated startup environment.

Own and grow strategic Financial Services accounts through executive relationship management, consultative selling, renewals, and expansion. Lead commercial strategy, SOWs, negotiations, QBRs, delivery governance, escalations, and value realization. Coordinate delivery, sales, solutions, cloud, and Databricks partners while managing scope, budgets, timelines, margins, retention, profitability, and customer satisfaction. Translate Databricks, data engineering, analytics, ML, AI, and cloud transformation capabilities into measurable business outcomes.

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

Lead data science projects from ideation through enterprise impact, building scalable and well-tested solutions that improve healthcare outcomes. Apply probability, statistics, machine learning, SQL, and Python to develop data-driven products and insights. Partner with stakeholders, assess product performance, identify strategic improvements, mitigate risks, and mentor teammates while aligning initiatives with business objectives.

Own and build Nectar Social’s React Native mobile platform for iOS and Android. Responsibilities include establishing architecture, shared components, testing, CI/CD, performance standards, monitoring, and error tracking. The engineer will develop AI-powered experiences, integrate social and e-commerce APIs, support real-time data-intensive features, and collaborate with product, design, and company leadership to shape the product and technical direction.

Lead research and development for Harris School Solutions’ K12 products, managing 40+ onsite, offshore, and remote employees. Set product and technical roadmaps, scale AI-assisted development, deliver AI-enabled capabilities, oversee cloud and Microsoft-stack engineering, and establish responsible AI governance. Manage budgets, P&L considerations, portfolio delivery, hiring, coaching, performance, and executive communication while improving development productivity, quality, and operational efficiency.

Build and productionize traditional machine learning models, owning feature engineering, validation, deployment, monitoring, drift detection, and retraining. Develop LLM-powered agentic tools, dashboards, self-serve analytics products, and automated insight pipelines. Partner with engineering and business stakeholders, write production-grade Python and SQL, drive adoption, improve data quality, and establish responsible AI workflows for a regulated industry.

Own end-to-end strategy, roadmap, delivery, adoption, safety, and commercial readiness for AI-native cybersecurity products. Conduct customer and partner discovery, lead 0-to-1 launches, define experimentation and evaluation frameworks, and collaborate with engineering, design, sales, finance, and executives. The role requires hands-on LLM product expertise, strong judgment in ambiguous environments, and a focus on trusted AI experiences for security professionals and MSP/MSSP partners.

Lead end-to-end product design for an AI-powered women’s health platform. Responsibilities include defining UX vision, creating interaction models, information architecture, wireframes, high-fidelity interfaces, prototypes, design systems, and user research. Collaborate with product, engineering, ML, marketing, and leadership teams to translate business needs into customer-focused solutions, manage design initiatives, and measure product success through user feedback and metrics.

Leads the transformation of Sophos’s pricing operations by building a centralized function, establishing pricing governance and review cadences, developing AI-assisted competitive and discount analysis capabilities, and aligning pricing across SecOps and Network Security. The role provides executive market visibility, defines performance metrics, supports organizational change, and builds a high-performing team serving sales, finance, and customer-facing stakeholders.

Own the strategy, roadmap, and investment priorities for foundational agricultural data products, including pipelines, data models, APIs, and shared services. Partner with engineering, architecture, data science, and product teams to deliver scalable, governed, high-quality data capabilities. Prioritize initiatives based on customer and commercial value, define success metrics, resolve cross-team tradeoffs, and expand data support for analytics, predictive modeling, machine learning, and AI applications.

Lead end-to-end LLM inference performance across serving systems, models, GPU hardware, and workloads. Define rigorous benchmarks, diagnose bottlenecks from scheduling through kernels and interconnects, optimize single- and multi-node deployments, and deliver production-ready runtimes and configurations. Collaborate with product and infrastructure teams, evaluate inference technologies, and implement runtime fixes. The role requires strong Python engineering, production experience with serving engines such as vLLM or SGLang, GPU profiling, and knowledge of modern inference optimization techniques.