Top Senior Machine Learning Jobs in Greensboro, NC

Build and maintain Safari AI’s cloud infrastructure, including production services, system design, reliability, documentation, and security compliance. The role sets technical direction for the cloud stack, collaborates with engineering and operations teams, improves development processes, and delivers incremental features. Candidates should have 4–6 years of software engineering experience, public cloud expertise, and experience taking complex services from concept through production. Streaming processing and machine learning experience are advantageous.

Design, develop, implement, support, and improve financial-system integrations, databases, reporting solutions, and automated processes. Lead technical financial systems projects from requirements gathering through implementation, focusing on Aderant Expert, SQL Server, SSIS, SSRS, and T-SQL. Collaborate with Finance, IS, vendors, and business stakeholders; troubleshoot complex data issues, optimize database performance, document technical solutions, and support multiple concurrent initiatives.

Own Litify’s AI Call Intelligence product line end to end, including call capture, transcription, summaries, conversational insights, voice agents, and agentic workflows. Define the roadmap, quality standards, guardrails, and evaluation practices; lead client discovery, beta programs, competitive research, backlog prioritization, and cross-functional delivery. Partner with engineering, design, data science, and go-to-market teams to launch products, drive adoption, and measure outcomes.

Leads Sophos’s Americas MSP channel strategy, revenue growth, partner productivity, and operating performance. Oversees recruitment, onboarding, enablement, retention, distribution relationships, recurring-revenue forecasting, strategic negotiations, and program optimization. Builds and coaches direct and matrixed teams while influencing product, pricing, investments, and partner-program decisions. Uses performance data and market intelligence to improve activation, adoption, retention, expansion, and return on investment across cybersecurity managed-service offerings.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Leads complex enterprise SaaS delivery programs for major banks, owning governance, client and executive relationships, commercial controls, risk management, regulatory deadlines, third-party coordination, and successful go-live. The role requires deep financial crime compliance technology experience, including AML, KYC, transaction monitoring, sanctions screening, or case management platforms, plus proven Tier 1 bank implementations, program turnaround expertise, cloud delivery, and senior stakeholder credibility.

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.

Leads Tala’s Machine Learning Engineering team in building and operating platforms for model development, real-time inference, streaming features, batch processing, deployment, monitoring, and production reliability. Manages and develops 4–6 engineers, owns delivery and prioritization, provides architectural leadership, improves engineering practices and SLOs, and partners with Data Science, Data Engineering, Product, Credit, and Business Development teams.

Consult as a fractional data scientist for hedge funds, private equity firms, and family offices. Lead data science initiatives: build infrastructure, develop and deploy models, create portfolio dashboards, monitor post-deployment performance, and partner with investment teams to turn data into actionable investment insights. Advise on vendor selection, data quality, technology stacks, KPIs, and governance.

Lead positioning, messaging, go-to-market strategy, launches, channel enablement, competitive intelligence, and analyst relations for Sophos’ AI cybersecurity solutions. Translate complex technical capabilities into buyer- and partner-focused narratives, build launch assets and sales tools, and coordinate cross-functional execution across product, sales, marketing, and research teams. The role also develops customer feedback loops, competitive battlecards, and category-defining market perspectives.

Leads the development of partner enablement programs for Databricks and Snowflake ecosystems. Establishes strategies, governance, stakeholder relationships, learning pathways, workshops, bootcamps, champion networks, and readiness frameworks for technical and business audiences. Translates data, AI, analytics, and lakehouse use cases into scalable learning experiences, aligns programs with partnership growth objectives, measures engagement and effectiveness, and continuously improves initiatives based on partner feedback and business impact.

The Enterprise Account Executive will drive revenue growth by managing complex sales cycles, closing deals with Fortune 500 companies, and understanding both technical and business needs.

Founding Engineer responsible for building FilmoreAI’s production AI and data platform for construction equipment dealers. The role covers agent infrastructure, model routing, LLM extraction and reasoning, canonical data modeling, entity resolution, Python data pipelines, Azure cloud orchestration, evaluation, observability, and safe human-approved write-back. The engineer will work independently in an ambiguous startup environment and use agentic development tools to ship reliable systems with strong cost, latency, accuracy, and operational guardrails.

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.

Build and deploy scalable AI and machine learning products for clinical research, including patient recruitment, enrollment forecasting, and study feasibility. Develop ML models, LLM-powered agents, data pipelines, and MLOps infrastructure using cloud services and CI/CD automation. Collaborate with cross-functional teams to integrate AI into clinical research workflows, monitor model performance, and advance reliable, unbiased solutions that improve patient outcomes.

Leads Yahoo’s Detection Engineering team within Threat Detection and Response. Responsibilities include developing cybersecurity detection strategy, managing detection engineers, building and maintaining detection rules, supporting investigations, conducting threat hunting and purple-team activities, integrating threat intelligence, and applying data science and AI to identify adversaries. The role also guides sprint delivery, researches emerging threats, and collaborates with security leadership, incident response, insider threat, and advanced cyber threat teams.

The Senior Data Scientist will analyze large-scale customer data, investigate behavioral questions, design and automate studies, and translate findings into actionable recommendations. The role includes maintaining analytics frameworks, documenting methodologies, writing white papers, and communicating insights across the company. Candidates should be independent, comfortable with ambiguity, and experienced with SQL and Redshift. Python or R, machine learning, Spark, A/B testing, and cross-functional experience are preferred.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.

Lead the roadmap and delivery of an AI data platform supporting internal teams and external healthcare products. Manage ML and LLM platform workstreams across data ingestion, training, deployment, monitoring, and workflow optimization. Partner with AI engineers, researchers, data scientists, clinical leaders, and business stakeholders to define requirements, develop user stories, validate model performance, and turn proofs of concept into scalable production capabilities.

Provide legal support for commercialization and product development of an AI-powered ad tech platform: draft and negotiate commercial agreements, manage IP portfolio and complex IP litigation, advise on AI, data, and privacy matters, counsel product teams on compliance and IP protection, and develop automated legal workflows.

Leads client services and cross-functional delivery teams supporting enterprise software implementations. Oversees end-to-end project execution, client relationships, business-process transformation, stakeholder education, requirements documentation, and ongoing value delivery. Applies revenue growth management expertise across pricing, trade promotions, assortment, or supply planning, while collaborating with technical teams on AI, machine learning, and analytics solutions.

Own product marketing for Gladly’s Agent Harness and AI Core platforms. Develop technical positioning, messaging, launch strategies, sales enablement, competitive intelligence, and narrative assets. Translate AI agent behavior, evaluation, steering, and measurement into credible messaging for CX leaders and technical buyers. Manage tier-one launches end to end while balancing two product areas as a senior individual contributor with minimal oversight.

Leads and develops a perception and machine learning engineering team building computer vision, sensor fusion, tracking, detection, and scene-understanding capabilities for autonomous systems. Owns roadmap planning, technical decisions, delivery, model development and deployment workflows, field readiness, hiring, performance management, and cross-functional execution with autonomy, embedded, data, hardware, product, programs, and field operations teams.