Top Senior Machine Learning Jobs in Charleston, SC

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

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 and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

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

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 and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

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 global GTM enablement for a Databricks product area, creating scalable technical content, competitive narratives, demos, labs, AI-powered tools, and learning programs for Solutions Architects and partner technical sellers. Partner with Product and Engineering to translate roadmaps into field-ready assets, establish feedback loops, measure field readiness and deal outcomes, and support selected customer-facing engagements. Build enablement programs from scratch while remaining hands-on with data and AI platforms.

Own Linktree’s production AI platform, including pipelines, model and prompt versioning, evaluations, monitoring, rollback, cost, latency, and reliability. Drive internal AI adoption through tooling, agent workflows, and enablement across Product, Engineering, Marketing, and Support. Establish practical governance for data handling and vendor risk, make build-versus-buy decisions, align AI investment with business priorities, and mentor engineers and analysts.

Design, productionize, and scale machine learning and optimization models, pipelines, libraries, and deployment platforms. Partner with data scientists, engineers, product managers, and business stakeholders to deliver ML capabilities, personalization systems, and reusable end-to-end workflows. Establish ML engineering best practices, troubleshoot data pipelines, mentor junior professionals, and help define BetterHelp’s ML platform strategy.

Manage enterprise metadata, business glossaries, data catalogs, and end-to-end data lineage for a federal case management modernization program. Configure governance and metadata platforms, integrate data sources and pipelines, establish standards and workflows, monitor metadata quality, support compliant data sharing, develop governance metrics, document procedures, and train data stewards and business users.

Own customer outcomes from discovery through production deployment. Build decision systems using ontologies, reasoning, graph analytics, optimization, and machine learning over enterprise data. Write Python, SQL, and PyRel; debug unfamiliar systems; tune performance; harden deployments; document reusable solutions; and upstream platform improvements. Lead technical workshops and proofs of concept while partnering closely with customers, Product, and Engineering.

Drive new-logo sales and revenue growth for Wonderlic’s talent assessment and employee development solutions. Identify and prospect target clients, build relationships with HR and recruiting decision-makers, manage opportunities through the full sales cycle, close new business, and transition customers to Customer Success. Maintain expertise in products, market trends, and competitive conditions while providing strategic insights. The role requires B2B SaaS and HR technology sales experience, quota achievement, pipeline generation, and experience selling to SMB, mid-market, and enterprise buyers.

Own strategic partnerships with CPG customers, driving measurable outcomes, platform adoption, user expansion, and retention. Analyze usage data and business context to identify risks and opportunities, develop success plans, lead executive and operational relationships, and advocate for customers internally. Collaborate with product, sales, marketing, and support teams while contributing to repeatable playbooks, thought leadership, and customer best practices.

Leads the vision, roadmap, and development of an AI-enabled Service Catalog platform. Combines product leadership with hands-on full-stack engineering across web applications, APIs, integrations, workflows, and AI features. Manages engineering and product strategy, defines success metrics, partners with architects and stakeholders, prototypes capabilities, and ensures scalable, secure, responsible solutions with human oversight.

Lead healthcare and pharmaceutical marketing analytics: analyze CRM, media, healthcare and behavioral data; build segmentation, attribution, audience scoring, and predictive models; develop measurement frameworks; use Python, SQL, BI and automation; translate insights for executives; mentor juniors and partner with Strategy, Media, and Client Services.

Conduct applied research on scalable optimization and resource-allocation algorithms for large communication networks. Apply machine learning, reinforcement learning, integer optimization, graph-based methods, and metaheuristics to improve solution quality and efficiency. Collaborate with software engineers to integrate algorithms into production aerospace networking systems, evaluate performance at realistic scale, publish research, support patent applications, and document novel methods.

Manage the operational integrity of an automated group health insurance underwriting workflow. Review and approve RFPs, validate broker and external data, correct errors, monitor funnel and risk metrics, analyze quote-to-bind performance, triage inquiries, coordinate with sales and health plan operations, and maintain underwriting dashboards and reporting.

Own product strategy, roadmap, problem definition, prioritization, and outcomes for a core platform area. Partner with engineering, data science, Product Owners, Product Marketing, sales, clients, and leadership to deliver data- and AI-driven capabilities. Define business cases, requirements, success measures, and go-to-market support while incorporating customer feedback, adoption data, regulatory considerations, and compliance requirements.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.