Top Senior Machine Learning Jobs in Raleigh, NC

Develop and deploy AI-driven applications, workflows, integrations, and ServiceNow solutions for enterprise customers. Gather requirements, configure and script ServiceNow modules, implement Now Assist and other AI capabilities, integrate external systems through REST, SOAP, MID Servers, and ETL, and support testing, documentation, deployment, incident remediation, service mapping, and event management. Collaborate with stakeholders and technical leads while maintaining consistent platform patterns.

Designs and builds highly scalable, fault-tolerant Azure compute services, microservices, REST APIs, billing pipelines, and distributed systems. Responsibilities include improving availability, security, scalability, performance, disaster recovery, and compute utilization; using telemetry and data-driven insights; developing cloud-native solutions with containers, NoSQL, and Big Data technologies; and leveraging AI-assisted development in an Agile environment.

Product Counsel will advise product, engineering, data science, marketing, compliance, and sales teams throughout the product lifecycle. Responsibilities include counseling on regulatory compliance, privacy, intellectual property, consumer protection, AI and machine learning, data rights, platform architecture, APIs, identity and account security, and marketing. The role translates legal requirements into technical guidance, supports AI governance, monitors evolving laws, and develops scalable legal processes for a fast-paced technology company.

Leads financial strategy, planning, forecasting, and operating cadence across Sales, Marketing, Customer Success, and GTM Operations. Owns GTM economics, sales compensation, commissions forecasting, executive reporting, driver-based modeling, resource allocation, and profitability analysis. Modernizes Finance through AI, automation, advanced analytics, improved controls, and scalable processes while developing the GTM Finance team and advising senior executives.

Leads automated scoring and natural language application research for educational assessment products. Responsibilities include setting team priorities, mentoring scientists, designing and analyzing studies, developing machine learning applications, collaborating with stakeholders, presenting technical findings, writing reports, publishing applied research, and supporting products involving automated scoring, crisis-content detection, and formative feedback.

Leads customer-facing technical delivery from demonstrations and requirements discovery through architecture, implementation, testing, and production launch. Builds AI-driven agents, analytical products, predictive modeling workflows, and data pipelines; integrates solutions with client CRMs, consumer applications, and varied data sources. Partners with client technical teams, presents to senior stakeholders, and feeds field learnings back to the core platform team. Requires occasional travel and strong Python, TypeScript, architecture, cloud, and communication skills.

Design, build, and support high-throughput, low-latency LLM inference and data pipelines; collaborate with data scientists to post-train and evaluate models; implement scalable, production-ready systems with strong testing, monitoring, and performance focus; mentor engineers and iterate on architecture, reliability, and user-facing AI applications.

Lead the strategy, roadmap, launch, adoption, and ongoing improvement of an AI-powered clinical data insights platform. Partner with Data Science, Engineering, and application teams to create reusable capabilities, define platform metrics, prioritize investments, evaluate build-versus-buy decisions, and align senior stakeholders across clinical, technical, and business objectives.

Own the technical sales cycle for Databricks consulting engagements, including discovery, architecture design, solution scoping, estimation, proposals, demos, proofs of concept, workshops, and statements of work. Design lakehouse, data engineering, analytics, governance, security, and AI architectures. Partner with sales, Databricks, alliance, and delivery teams while ensuring effective handoffs into implementation.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

Supports payer modernization and health services consulting engagements by analyzing operational challenges, optimizing processes, applying business analytics, engaging stakeholders, implementing quality standards, and guiding transformation initiatives. Develops operational support frameworks, conducts market research, manages change, and advises clients on improving service delivery and business performance while mentoring junior team members.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Conducts econometric, causal, statistical, and optimization analyses to improve operational efficiency, resource allocation, product performance, and business outcomes. The role defines efficiency measures, develops forecasting and optimization tools, partners with product and engineering teams on data instrumentation and implementation, and communicates findings to executives through clear reports.

Senior Business Systems Analyst to define requirements for agent-facing servicing applications, design integrations/APIs with core banking systems, translate needs into user stories and acceptance criteria, improve agent workflows and productivity, and identify AI/ML opportunities for fraud detection, automation, and operational analytics. Supports testing, validation, and releases.

Build and deploy mechanistic, hybrid, and data-driven models for pharmaceutical CMC processes, including drug substance, drug product, packaging, labeling, technology transfer, and manufacturing. Integrate process and experimental data into FAIR data products, analytics, dashboards, and AI-enabled tools. Partner with technical teams and CDMOs to support process understanding, forecasting, risk assessment, regulatory filings, and technology-transfer decisions while owning the digital roadmap and mentoring colleagues.

Senior Product Manager responsible for FinCrime product strategy and delivery across fraud prevention, scams, payment risk, vendor integrations, and cryptocurrency-related products. Owns the full product lifecycle, global feature rollouts, stakeholder management, metrics, regulatory alignment, and customer experience. The role requires hands-on experience with fraud analytics, risk and financial modeling, machine learning, AI tools, APIs, payment systems, and financial-services compliance.

Deploys, integrates, and scales enterprise Generative AI solutions across Azure environments. The role develops LangGraph agentic workflows, fine-tunes and evaluates LLMs, reduces hallucinations, integrates retrieval systems and APIs, and collaborates with customer engineering teams. Responsibilities also include requirements documentation, process mapping, automation engineering, software architecture, and communicating business value.

Lead the vision, roadmap, and delivery of DealCloud Activator and legal vertical applications. Manage product strategy, client discovery, prioritization, engineering backlogs, quarterly releases, AI and machine-learning enhancements, and build-versus-buy decisions. Partner with executives, clients, sales, marketing, and go-to-market teams to deliver CRM and deal-management solutions for law firms and professional-services organizations.

Own and improve Quora’s second-phase ranking models for feed and digest experiences. Build end-to-end machine learning systems covering data pipelines, candidate extraction, feature engineering, model training, and production integration. Identify new product applications for machine learning, develop efficient algorithms with other ML engineers, and contribute methodologies for large-scale recommendation systems.

Own the vision, roadmap, and delivery of AI-enabled finance technology products. Translate finance and accounting challenges into scalable digital solutions using data, cloud, analytics, automation, and AI. Partner with senior stakeholders to prioritize outcomes, lead cross-functional delivery, monitor product performance, and improve adoption, usability, anomaly detection, insight generation, and data-driven financial decision-making.

Leads customer-facing development of AI agent systems, multi-agent workflows, BI and ML pipelines, and enterprise data governance solutions. Partners with Fortune 500 stakeholders to translate business and data challenges into production-grade technical solutions, develops reusable delivery patterns and internal tooling, influences product roadmaps, conducts competitive analysis, and mentors engineers and technical teams.

Build and operate production machine learning systems for Safety AI, including low-latency APIs, data pipelines, model serving, evaluation, monitoring, and rollout infrastructure. Process large-scale camera and telematics data, optimize cloud and edge-to-cloud execution, track model performance and drift, and partner with applied scientists, firmware engineers, platform teams, and product managers to deliver reliable safety features.

Design, build, and optimize personalized recommendation systems for Fortnite Discover, including candidate generation, ranking, reranking, user representations, and impression allocation. Develop deep learning retrieval models, run A/B experiments, establish evaluation frameworks, and deploy models to production. Collaborate on content quality and ranking signals while making infrastructure decisions across batch, near-real-time, and streaming architectures.

Design, build, and optimize personalized recommendation systems for Fortnite’s Discover experience. Develop retrieval, ranking, reranking, user representation, and candidate-generation models using deep learning. Lead A/B experimentation, evaluation frameworks, production deployment, and ML infrastructure decisions across batch, near-real-time, and streaming systems. Collaborate on content quality and ranking signals while balancing relevance, diversity, fair exposure, cold-start challenges, and creator incentives.

Serve as strategic commercial and technology legal advisor, drafting and negotiating software, SaaS, licensing, data, customer, and vendor agreements. Advise on AI products, governance, responsible AI, privacy, intellectual property, regulatory compliance, product launches, and legal risk mitigation. Partner with Sales, Product, Engineering, and executive teams while supporting international and broader legal initiatives. Use legal technology and AI tools to improve legal service delivery.