Top Senior Machine Learning Jobs in Nashville, TN

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Drives strategic business development and complex sales opportunities for automation, intelligence, and digital transformation solutions serving municipal water and wastewater systems. Builds relationships with municipalities, consulting engineers, and industry partners; provides technical consulting; develops proposals; negotiates contracts; manages sales pipelines; and collaborates with engineering, cybersecurity, project management, and product teams. The role requires expertise in SCADA, instrumentation, control systems, AI analytics, and water infrastructure, along with travel to customer sites and industry events.

Lead technical pre-sales for large Oil, Gas & Energy accounts, define and implement Databricks-based data and ML/AI strategies, build technical champions, mentor teammates, and drive enterprise adoption through technical leadership and value selling.

Own G2’s research agenda for evaluating AI agents in realistic business workflows. Design benchmarks, task environments, scoring systems, automated and human grading methods, and reliability analyses. Collaborate with engineering and product teams to ship evaluation capabilities, communicate findings to customers and researchers, mentor technical teams, and establish repeatable standards. The role requires hands-on LLM and agent evaluation experience, original research, statistical judgment, product delivery, and technical leadership.

Lead product strategy, roadmap execution, and measurable outcomes for an AI-enabled refinance title decisioning platform. Translate strategy into requirements, user stories, and acceptance criteria; prioritize initiatives against OKRs; and partner with engineering, data science, operations, sales, and marketing. Monitor product health, accuracy, costs, service levels, and performance through metrics and dashboards. Manage stakeholders, customer onboarding, continuous improvement, and automation opportunities across a regulated real estate workflow.

Own and scale Tilt’s credit card acquisition through affiliate partnerships, paid search, and paid social. Lead channel strategy, partner launches, targeting, experimentation, and optimization while collaborating with credit, data science, product, engineering, and marketing. Use SQL and Python to evaluate funnel performance, unit economics, approvals, activation, spend, and credit outcomes. Shape acquisition policies and application experiences to drive profitable growth.

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.

Designs, deploys, and maintains AI and machine learning solutions, including generative AI, LLM, RAG, and conversational AI applications. Owns agentic engineering infrastructure, application guardrails for patient-care workflows, data pipelines, analytics, model governance, monitoring, and cloud deployment. Provides architectural leadership, improves engineering throughput, ensures privacy and compliance, and translates business needs into scalable AI solutions.

Designs, implements, and maintains automated security detection, orchestration, and integration capabilities for USPS. Analyzes security telemetry, identifies anomalies and detection gaps, enhances detection content, validates workflows, and supports SOC, threat intelligence, and incident response teams. The role also translates operational needs into technical solutions, researches emerging security and machine-learning capabilities, and maintains documentation, runbooks, and procedures.

Lead product positioning, go-to-market strategy, launches, customer insights, competitive intelligence, messaging, sales enablement, and thought leadership for AI-driven cybersecurity and authentication products. Translate complex AI and machine learning technologies for technical and business audiences, manage marketing plans and budgets, support customer case studies, and mentor a high-performing product marketing team. Partner closely with Product, Engineering, Sales, Marketing, and executive leadership.

Coordinates strategic AI programs across engineering, product, legal, risk, compliance, security, HR, and business teams. Develops execution plans, governance frameworks, status reporting, risk registers, and executive communications. Supports AI platform and agent deployment initiatives, AI policy development, enterprise training, stakeholder alignment, and adoption. Requires strong program management, AI technology understanding, organizational skills, and experience managing complex cross-functional initiatives.

Leads the scientific direction and technical roadmap for a permanent magnet research vertical. Responsibilities include guiding computational materials discovery and AI modeling, developing manufacturable magnet formulations, building and mentoring multidisciplinary teams, managing intellectual property, coordinating national laboratory and industry partnerships, and connecting simulation with experimental validation. The role also supports commercial licensing, external scientific communications, publications, and federally funded research programs.

Own the strategy, roadmap, and success metrics for AI security capabilities across the Pathfinder platform. Serve as the internal expert on agentic AI threats, identity security, and emerging attack techniques. Define requirements for securing AI agents, MCP servers, and orchestration frameworks; conduct market and competitive research; lead design partner programs; coordinate cross-portfolio product work; and support analyst, customer, marketing, and pre-sales engagements.

Owns a portfolio of NovaOS capabilities from concept through delivery, adoption, and continuous improvement. Manages backlogs, roadmaps, prioritization, requirements, user stories, release planning, and product metrics. Partners with stakeholders, Engineering, AI, UX, Data Science, and Architecture teams to deliver enterprise AI-enabled products aligned with governance, Responsible AI, and business objectives.

Own and improve ClickUp’s voice AI systems, including real-time speech-to-text, audio processing, context-aware transcription, LLM post-processing, mention resolution, formatting, and voice-to-action workflows. Evaluate and integrate ASR models for accuracy, latency, and cost, while collaborating across product and platform teams to deliver voice and multimodal assistant features across desktop, mobile, web, and browser extension products.

Leads enterprise CrowdStrike deployments, architecture, compromise assessments, threat hunting, SOC modernization, detection engineering, cyber analytics, Purple Team exercises, and incident response. Advises CISOs and executives, manages cross-functional teams, designs global 24/7 SOCs, and coordinates breach containment and recovery. Requires deep CrowdStrike expertise, cybersecurity leadership, scripting, network and detection engineering, and executive communication skills.

Designs and maintains scalable data models, semantic layers, ETL/ELT workflows, data-quality frameworks, and governed analytics products for commercial operations. Owns data solutions from requirements through deployment, monitoring, documentation, and support. Partners with technical and business stakeholders to deliver trusted reporting, dashboards, scorecards, productivity measurements, and AI-enabled decision support.

Build, productionize, and govern clinical machine learning products using large-scale healthcare data. Responsibilities include developing predictive models, monitoring ML research, supporting MLOps, implementing model governance, integrating analytics into products and dashboards, curating datasets, partnering with clinicians and product teams, mentoring engineers, and communicating findings to technical and executive stakeholders.

Designs, builds, and operates observability and SRE systems that improve IT service visibility, reliability, performance, and resilience. Responsibilities include metrics collection, monitoring, alerting, APM, RUM, synthetic transactions, SLOs, incident response, capacity planning, infrastructure automation, self-healing systems, and production readiness reviews. The role also applies AI-enabled operations, supports on-call rotations, reduces operational toil, and partners with development teams on architecture and chaos testing.

Leads enterprise security reviews, threat modeling, architecture assessments, governance, and control development for AI, generative AI, machine learning, LLM, RAG, and AI-agent solutions. Defines security standards and guardrails, evaluates platforms and vendors, advises cross-functional stakeholders, and supports responsible AI adoption while managing cybersecurity, privacy, regulatory, and operational risks.

Drive new business revenue across the Western Territory by selling complex healthcare technology and services, including AI-enabled EHR and revenue cycle management solutions. Manage the complete enterprise sales cycle from prospecting, discovery, demonstrations, proposals, negotiations, and closing through accurate forecasting and CRM updates. Build relationships with healthcare decision-makers, manage RFPs, develop territory plans, and travel 50–75% of the time.

Own cloud security across AWS and Azure, including identity, network, application, container, data, and AI security. Build policy and infrastructure controls as code, integrate security into CI/CD, protect regulated health data, and manage detection, incident response, vulnerability remediation, and compliance. The role also develops AI security guardrails and coaches engineering teams while operating production security controls and supporting on-call responsibilities.

Leads enterprise AI solution strategy, architecture, pre-sales, and implementation delivery for customers across the Americas. Defines AI use cases, validates feasibility, designs scalable architectures, guides Professional Services teams, and resolves complex technical challenges. Develops AI service offerings, methodologies, reusable assets, and enablement programs while mentoring architects, consultants, and project leaders. Requires deep experience with enterprise transformations, LLMs, multi-agent systems, generative AI, data architecture, cloud platforms, and production AI deployments.

Own enterprise technical deployment roadmaps, milestones, acceptance criteria, governance, and post-launch adoption. Coordinate Product, Engineering, Delivery, Support, and Sales teams to resolve blockers, manage resources, map workflows, track KPIs, and demonstrate ROI. Partner with account executives on technical expansion opportunities and establish scalable deployment playbooks, PMO templates, and integration patterns.

Own the vision, strategy, and roadmap for Root’s pricing platform and machine learning infrastructure. Lead engineering and partner with data science, actuarial, and engineering teams to improve pricing workflows, model development, deployment, monitoring, and regulatory operations. Drive self-service tooling, LLM-enabled data science workflows, platform reliability, and nationwide expansion while translating business needs into product requirements and prioritized investments.