Top Remote Machine Learning Jobs in Columbus, OH

Own the full Global System Integrator partner lifecycle, including sourcing, agreements, joint go-to-market motions, enablement, delivery planning, and performance optimization. Build relationships across major GSIs such as Accenture, Deloitte, Bain, BCG, Slalom, and IBM. Collaborate with sales, product, and engineering teams to generate partner-sourced and influenced pipeline and revenue. Develop the GSI strategy, playbook, and operating processes for Sequen’s growing AI business.

Drive revenue retention and account growth across a portfolio of advertising clients. Responsibilities include developing account growth plans, managing forecasts and pipelines, identifying upsell and cross-sell opportunities, fostering product adoption, delivering data-driven campaign insights, leading QBRs, and coordinating Analyst, AdOps, Product, and Creative teams to resolve issues and achieve client outcomes.

Own the strategy, roadmap, packaging, pricing, design partnerships, and go-to-market launch of brightfin’s AI-native FinOps and ITFM product pillar. This individual contributor role will define the MVP, validate market demand, secure initial revenue, and scale the offering toward meaningful ARR. The leader must have extensive AI product leadership experience, direct ITFM/TEM/FinOps expertise, enterprise governance knowledge, and proven ownership of pricing, positioning, sales enablement, and commercialization.

Own strategic enterprise customer relationships, driving adoption, retention, measurable value, and expansion. Lead success reviews and executive engagements, translate supply chain challenges into solution strategies, build prototypes in Lyric Studio, train customer teams, coordinate forward-deployed engineers, partner with Sales on growth opportunities, and relay customer needs to Product and Engineering. The role requires deep supply chain expertise, technical fluency in modeling, planning, or AI/ML, and strong executive relationship skills.

Lead research and development of generative AI and recommendation solutions for Netflix promotional assets and content discovery. Responsibilities include tracking LLM research, developing summarization and LLM-as-judge systems, training and evaluating models, optimizing generated content for audience impact, partnering with engineering teams, defining ML roadmaps, and communicating technical strategies to stakeholders.

Leads innovation and enterprise solution strategy for healthcare payment integrity, developing scalable platforms using AI, automation, analytics, and data technologies. Engages senior clients, supports strategic pursuits, shapes transformation roadmaps, and builds partnerships. Oversees solution architecture, enterprise system development, prototyping, governance, performance metrics, and commercialization. The role also mentors cross-functional teams and translates complex healthcare payer challenges into differentiated, market-ready solutions.

Architects and rapidly deploys AI agent systems, BI and ML pipelines, and data governance solutions for strategic enterprise customers. Acts as a technical bridge between customers, Product, Engineering, and GTM teams; develops reusable solution patterns and internal tooling; influences platform roadmaps and delivery methodologies; conducts competitive analysis; and mentors field and customer technical teams.

Manage post-sales relationships with strategic customers, drive adoption and business outcomes, coordinate technology delivery projects, oversee customer issues and escalations, facilitate customer meetings and Quarterly Business Reviews, communicate customer needs internally, and track customer status and KPIs. The role supports financial institutions across North America and partners with technical, threat analysis, data science, product, and engineering teams.

Leads the software engineering organization responsible for scalable, reliable applications and systems integrating hardware, embedded software, edge computing, cloud infrastructure, and machine learning. Sets technical strategy, develops engineering leaders, drives product delivery, establishes engineering standards, and ensures operational excellence across national-scale deployments. Partners with Product, Deployment, Data Science, and executive leadership to align roadmaps, resolve risks, and build high-performing distributed teams.

Lead product strategy, roadmap execution, discovery, and delivery for Records Request Management and FOIA solutions. Define AI-enabled capabilities such as document discovery, automated redaction, classification, workflow optimization, and self-service. Partner with engineering, design, security, compliance, legal, sales, and customer teams to deliver secure, compliant products for federal and regulated public-sector customers. Translate FOIA and records-access requirements into product outcomes while supporting adoption, growth, and market expansion.

Develop complex healthcare reports, ETL solutions, databases, and Power BI dashboards for LTSS and Dual Eligible programs. Analyze multidimensional data, ensure governance and accuracy, identify operational improvements, and deliver actionable insights to leadership. The role translates business requirements into scalable reporting solutions, collaborates with clinical, operational, data engineering, and IT teams, and leads testing, process automation, visualization, and large cross-functional data projects.

Drive go-to-market reporting, business intelligence, forecasting, dashboard development, and ad hoc analysis. The role standardizes forecasting processes, maintains analytical documentation, automates reporting and data pipelines using AI-assisted tools, and delivers actionable insights to Sales, Marketing, Engineering, Finance, and executive stakeholders.

Build and lead the organization-wide adoption of generative AI, agentic systems, and AI-assisted development. Design production automation agents, evaluate coding tools, modernize rules-based workflows with ML, and establish responsible AI guardrails. Partner with engineering, product, data, and clinical teams to identify high-impact opportunities, own the enablement roadmap, measure outcomes, and drive adoption through working software, documentation, and hands-on collaboration.

Supports responsible AI governance by developing frameworks, conducting fairness and risk assessments, monitoring regulatory requirements, maintaining compliance documentation, educating stakeholders, and improving AI oversight practices. Works across technical, legal, compliance, risk, and business teams to promote ethical, transparent, accountable, and trustworthy AI systems.

Leads business analysis for AI and automation initiatives, identifying adoption opportunities, developing business cases, gathering requirements, and aligning business needs with technical solutions. The role facilitates stakeholder workshops, supports solution design, testing, deployment, change management, governance, and benefits realization. It also advises executives, monitors outcomes, promotes business analysis standards, and mentors junior analysts.

Monitors and improves AI-powered systems by tracking performance, utilization, KPIs, incidents, and operational trends. Develops reports and dashboards, identifies efficiency opportunities, supports governance and compliance activities, documents procedures, and collaborates with AI engineers, product teams, business stakeholders, and operations leaders to resolve issues and improve adoption.

Annotates, labels, categorizes, validates, and quality-checks structured and unstructured data for AI model training. Maintains dataset accuracy, consistency, documentation, and version control while collaborating with AI engineers, data scientists, and quality teams. The role also supports annotation workflow management, guideline development, calibration exercises, error identification, and continuous process improvement.

Own the strategy, roadmap, development, delivery, and continuous improvement of AI-powered products. Translate business and customer needs into product requirements, coordinate engineering and AI teams, define success metrics, monitor adoption and ROI, and support responsible AI governance. The role also involves stakeholder management, leadership communication, market and technology evaluation, release planning, and ensuring successful product implementation.

Supports AI governance frameworks, policies, risk assessments, compliance reviews, monitoring, reporting, audits, and responsible AI practices. Partners with legal, compliance, security, AI, and business stakeholders to interpret regulations, establish controls, mitigate risks, and improve governance maturity. Tracks regulatory developments, maintains documentation, advises project teams, and promotes responsible AI adoption across the organization.

Assesses and mitigates security risks across AI, machine learning, and Generative AI systems. Responsibilities include threat modeling, vulnerability assessment, security monitoring, incident response, governance, compliance, access controls, policy development, audit support, and advising engineering and business teams on secure AI development and responsible adoption.

Leads operational oversight, performance analysis, governance, and continuous improvement for AI-powered products and services. Develops performance frameworks, executive dashboards, business insights, risk and compliance reporting, and scalable AI operating models. Partners with AI engineers, product teams, and business leaders to optimize workflows, support automation, manage operational risks, and drive cross-functional operational excellence.

Leads the strategy, roadmap, development, launch, and optimization of AI-powered products. Defines product vision, requirements, priorities, success metrics, and adoption goals while coordinating engineering, AI, business, executive, and customer stakeholders. Evaluates emerging AI capabilities, supports responsible AI governance, manages product performance, and drives continuous improvement aligned with business objectives.

Leads AI data annotation operations, managing workflows, resources, production targets, quality standards, audits, and performance metrics. Oversees annotation teams through coaching, recruitment support, onboarding, and performance management. Partners with AI engineers, trainers, product teams, and operational stakeholders to translate requirements into plans. Drives process improvement, automation, tool adoption, data integrity, and operational excellence across AI and machine learning data preparation initiatives.

Identifies business opportunities for AI and automation, gathers and documents requirements, develops business cases, supports solution design and delivery, facilitates stakeholder collaboration, assists with testing and change management, and tracks project outcomes, reporting, and benefits realization.

Owns AI product backlogs, priorities, requirements, user stories, and acceptance criteria. Translates business needs into technical solutions, coordinates stakeholders and delivery teams, supports Agile ceremonies and product releases, monitors adoption and performance, and drives continuous improvement. The role also identifies AI-driven business opportunities, supports responsible AI practices, and contributes to AI product strategy.