Top Senior Machine Learning Jobs in Raleigh, NC

Investigate complex AML cases, review transaction-monitoring alerts, determine SAR/STR filing decisions, and communicate findings to regulators, law enforcement, and stakeholders. The role also supports audits, improves AML detection models and typology coverage, analyzes transactional data, identifies financial crime trends, and provides analyst training. Candidates need strong blockchain, AML regulations, investigative writing, and blockchain forensic tool experience, with AI and SQL capabilities preferred or advantageous.

Leads BI and analytics development by designing, optimizing, and governing dashboards, analytical models, semantic layers, SQL queries, and stored procedures across Cognos, QlikView, and Power BI. Collaborates with business, data science, visualization, and engineering teams to prepare data, develop machine learning or exploratory analytics solutions, automate production workflows, and deliver actionable insights. Provides technical leadership, mentors team members, establishes standards, reviews work, and promotes reusable components and best practices.

Designs, prototypes, evaluates, and guides deployment of AI-enabled capabilities across ITSM offerings, especially Incident, Change, and Problem Management. Partners with product, engineering, architecture, platform, and governance teams to select appropriate automation, analytics, machine learning, generative AI, agentic AI, or API-based patterns. Creates solution artifacts, coaches teams, influences strategy, establishes scalable design patterns, and defines success measures while managing operational and risk considerations.

Leads the development and deployment of data solutions using Palantir Foundry and AIP. Manages engineering teams, coaches team members, oversees project planning and execution, analyzes system interactions, manages client relationships, and drives innovation. The role applies software engineering, data engineering, analytics, and AI/ML techniques to deliver scalable client solutions while maintaining technical and professional standards.

Leads the development and deployment of software and data solutions using Palantir Foundry and AI/ML technologies. Responsibilities include data engineering, analytics, system improvement, client account management, project ownership, team leadership, coaching, stakeholder engagement, and continuous improvement. The role requires building scalable applications with large datasets and delivering customer-focused solutions.

Own and grow strategic enterprise customer relationships, driving retention, renewals, expansion, and seven-figure software transactions. Develop multi-year account plans, build executive and technical stakeholder relationships, identify expansion opportunities, lead negotiations, maintain forecasts and pipeline visibility, and coordinate cross-functional teams. Engage with data scientists and AI/ML engineers to understand adoption, customer outcomes, and opportunities to expand platform usage across business units and use cases.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Leads GitLab’s Product Data Science team, setting its strategy, roadmap, analytical standards, and priorities. Partners with Product and Engineering leaders on experimentation, causal inference, analytics, and production modeling. Manages, hires, coaches, and retains data scientists while building a high-performing function. Provides hands-on technical review of models, analyses, and queries, and communicates insights and risks to senior leaders.

Deploys, configures, optimizes, and supports CrowdStrike Falcon’s AI-powered detection and response capabilities. The role tunes machine learning models, develops security automation playbooks, troubleshoots customer environments, integrates Falcon with existing tools, supports threat hunting and forensic analysis, and develops AI training and customer-facing materials. Requires extensive IT deployment, endpoint, security automation, operating system, AI/ML, scripting, and customer consulting experience, with travel up to 25%.

Develop and deploy production machine learning and AI solutions for customer-facing applications. Build proofs of concept, integrate open-source tools such as MLflow, Spark, LangChain, and Kubeflow on Kubernetes, optimize models, and improve product capabilities. The role requires developing AI agents, collaborating with product and engineering teams, mentoring junior staff, documenting practices, and communicating effectively with leadership and distributed teams.

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.

Analyzes the Security for AI competitive landscape, including AI detection and response, generative AI security, autonomous agents, prompt injection, and data leakage. Partners with Product, Sales, Marketing, Strategy, and senior leaders to guide product roadmaps, go-to-market strategy, deal support, sales tactics, and competitive positioning. Conducts win/loss analysis and translates complex AI and cybersecurity concepts into executive and field-actionable guidance.

Leads financial statement audits for digital assets and financial services clients, evaluating regulatory compliance, governance, risk management, and internal controls. Applies advanced auditing and technical accounting expertise to identify material misstatements and issue audit reports. Directs complex engagements, coaches diverse teams, manages client relationships, communicates findings, and reinforces professional, independence, and ethical standards. The role also involves data analysis and exploring AI and machine learning platforms to improve processes.

Provides technical account management for enterprise customers using Samsara’s IoT platform. Builds customer relationships, troubleshoots APIs, hardware, software, and AI technologies, manages significant incidents, aligns solutions with business needs, maintains account records, and serves as a trusted technical advisor. Collaborates with internal teams, supports customer growth, contributes to TAM team development, and provides occasional travel and after-hours coverage.

Define and own the technical vision, product strategy, roadmap, data strategy, and AI integration for CrowdStrike’s Next-Gen SIEM and log management products. Translate customer, market, and threat intelligence into shipped capabilities; lead cross-platform integration across endpoint, cloud, identity, and exposure products; and articulate the platform consolidation narrative. Engage executives, customers, analysts, sales, engineering, and product teams while driving detection, investigation, response automation, and cybersecurity thought leadership.

Build and maintain core infrastructure for developing, training, evaluating, deploying, and operating machine learning models and pipelines for Atlassian’s GenAI products. Solve complex software infrastructure and architecture challenges, lead engineers through technical projects from design to launch, and collaborate with internal teams and customers. The role involves large-scale distributed systems, data processing, cloud platforms, CI/CD, and machine learning lifecycle support.

Designs scalable data architectures, ELT/ETL pipelines, data models, quality frameworks, and self-service data platforms. Partners with engineering, product, program, leadership, and data science teams to translate business needs into technical solutions. The role includes end-to-end technical ownership, large-scale batch and streaming data processing, mentoring junior engineers, system optimization, and on-call support for platform stability.

Leads technical pre-sales for supply chain integration solutions, partnering with Sales to conduct discovery, design ERP/WMS/TMS and trading-partner architectures, run POCs, deliver demonstrations, and respond to RFPs. Advises technical and executive stakeholders on business outcomes and AI opportunities, translates capabilities into measurable ROI, and collaborates with Product, Customer Success, and Professional Services on roadmap feedback and post-sale handoffs.

Lead product strategy, roadmap, and delivery for Falcon Complete’s internal MDR tooling, including AI-powered investigation and triage, ticketing, case management, and analyst workbench systems. Partner with security operations, analysts, engineering, and data science teams to translate workflows into product requirements, prioritize automation, improve analyst productivity and response times, define success metrics, and enhance customer outcomes.

Advise clients on privacy, data protection, and responsible AI requirements. Evaluate AI systems for fairness, transparency, safety, privacy, accountability, and third-party risk. Develop governance operating models, policies, risk-tiering approaches, controls, impact assessments, and client deliverables. Interpret regulatory changes, support breach investigations, collaborate with legal, compliance, cybersecurity, data, and technology teams, and mentor junior staff. Apply technical literacy in AI/ML, GenAI, software development, technical architecture, and Python.

Verify ASIC inference accelerator designs at block and SoC levels using advanced methodologies, random stimulus, functional coverage, assertions, and UVM. Develop verification infrastructure, debug designs, optimize automated flows, and collaborate with architects, designers, and pre- and post-silicon teams. Apply knowledge of ASIC design flow, power verification, DFT, netlist verification, and machine learning techniques to improve verification processes.

Develop GPU-accelerated techniques for generative AI training and inference, optimize algorithms and performance across NVIDIA CPU and GPU architectures, contribute to frameworks, libraries, and open-source projects, and collaborate with developers, researchers, and hardware and software engineering teams. The role focuses on LLMs, diffusion models, multimodal systems, low-level optimization, and communicating innovations through technical publications and industry conferences.

Leads software engineering teams developing the Health100 consumer health platform. Responsibilities include architectural leadership for distributed systems, APIs, and AI-enabled capabilities; recruiting and mentoring engineers; managing initiatives through delivery and production operations; establishing performance, risk, and governance practices; and partnering across product, design, security, analytics, and business teams. The role emphasizes Java, cloud-native development, microservices, Generative AI, intelligent automation, and scalable platform solutions.

Drives revenue growth by selling Splunk and Cisco software solutions to large enterprise accounts. Responsibilities include landing, expanding, and deepening opportunities; building executive relationships; developing account plans; managing partners and channels; forecasting pipeline and revenue; coordinating complex deals; and collaborating with sales engineering, customer success, marketing, professional services, and leadership.

Leads client-facing generative AI and data modernization engagements, directing solution design, delivery planning, architecture, and technical decisions. Guides teams in prompt engineering, context engineering, agent orchestration, LLM evaluation, RAG, vector databases, and AI guardrails. Oversees cloud AI implementations using Gemini, Vertex AI, AWS Bedrock, or Azure AI Services; develops Python prototypes; evaluates model performance; manages workstreams and deliverables; and mentors staff on AI methods, agile delivery, and technical problem-solving.