Top Remote Machine Learning Jobs in Columbus, OH

Leads enterprise AI strategy and operations by building AI product portfolios, agentic workflows, copilots, intelligent applications, and human-AI experiences. Partners with executives, engineering, data science, security, and business teams to prioritize opportunities, establish roadmaps, redesign workflows, drive adoption, govern AI initiatives, and measure business value. Builds and leads AI product management teams while overseeing organizational change and cross-functional portfolio governance.

Drive new enterprise revenue and customer expansion by selling AI-powered SaaS solutions. Manage complex 6–12 month sales cycles, build executive relationships, develop value propositions, maintain pipeline accuracy, lead virtual account teams, and close high-value deals. Translate technical AI capabilities into measurable business outcomes, guide customer adoption, collaborate with marketing, product, and customer success teams, and exceed quarterly pipeline and revenue targets.

Lead product vision, strategy, discovery, and Agile delivery for insurance platforms. Partner with engineering, data science, design, QA, and insurance domain teams to prioritize opportunities, manage backlogs, evaluate build-versus-buy decisions, guide technical design, coordinate delivery, and measure outcomes. The role requires strong knowledge of insurance policy lifecycles, integrations, data modeling, pricing, underwriting, and AI-enabled workflows.

Leads product strategy, roadmap prioritization, AI and automation initiatives, client engagement, and cross-functional delivery for SPINS Intelligence and Portal. The role combines hands-on product management with PM team leadership, including writing user stories, defining acceptance criteria, triaging issues, reviewing sprint output, managing product economics, and developing business cases. Requires strong CPG, SaaS analytics, data product, AI/ML, and technical platform expertise.

Own Sophos EDR strategy, roadmap, technical product development, AI-powered experiences, and go-to-market execution. Translate customer needs, threat research, telemetry, competitive intelligence, and business goals into product priorities. Partner with engineering, security operations, threat research, marketing, sales, and customer success to deliver endpoint detection, investigation, threat hunting, response, reporting, and XDR/MDR upgrade capabilities while driving adoption, revenue, and customer outcomes.

Claims Counsel advises on auto insurance coverage, multi-state tort law, civil procedure, and litigation matters. Responsibilities include drafting coverage opinions, researching insurance laws, supporting claims policies and training, collaborating with legal and claims teams, conducting adjuster training, and drafting form letters and releases.

Lead the design and optimization of the VA VHA AI Education Hub, including its AI learning assistant, sandbox, integrations, analytics, and healthcare data models. Apply machine learning, synthetic data, privacy-preserving methods, and responsible AI practices in a secure federal healthcare environment. Collaborate with VA stakeholders and technical teams, document solutions, ensure governance and compliance, and present platform metrics and findings to leadership.

Advise the Department of Veterans Affairs on responsible AI strategy, governance, risk mitigation, lifecycle management, vendor evaluation, and operational adoption across healthcare use cases. Develop policies, playbooks, briefings, white papers, and decision memos for technical and executive audiences. Assess issues including bias, explainability, privacy, model drift, and patient safety while supporting federal AI compliance and enterprise transformation initiatives.

Leads the VHA AI Education Hub’s instructional systems design program, directing end-to-end curriculum development, training delivery, needs assessments, quality assurance, accessibility compliance, and stakeholder coordination. Manages and mentors instructional designers while establishing enterprise curriculum standards and governance. Develops AI literacy, ethics, and clinical application training for healthcare professionals, ensuring alignment with federal requirements, VA policies, and Section 508 accessibility standards.

Leads business architecture and requirements activities for a federal healthcare modernization portfolio. Facilitates stakeholder workshops, analyzes current and future-state processes, develops architecture artifacts and EDI documentation, translates business needs into functional and technical requirements, and supports data integration, migration, traceability, defect management, UAT, and process automation initiatives.

Serve as the senior AI advisor to the VHA National Artificial Intelligence Institute. Develop AI risk-management playbooks, governance guidance, risk stratification methods, enterprise AI strategies, training, and oversight materials. Advise AI use-case owners and government stakeholders, translate federal AI policy into actionable guidance, support health information and ModelOps initiatives, and research emerging AI governance practices. The role is remote, advisory, full-time, and contingent.

Manage the VHA AI Education Hub program and subordinate projects across the full lifecycle. Serve as the primary stakeholder contact, coordinate contractor teams and subject matter experts, maintain schedules, risks, status reports, and corrective actions, and lead government stakeholder meetings. Ensure timely, compliant delivery of AI education, training, and technology integration workstreams while meeting federal acquisition, VA security, and VHA requirements.

Architect and prototype scalable solutions for Twilio’s emerging technologies experimentation team. Lead AI, machine learning, and LLM-driven initiatives; guide technical direction; mentor engineers across the US and India; align prototypes with business goals; and ensure enterprise architecture, scalability, extensibility, and production readiness. The role requires extensive architecture or principal engineering experience, cloud expertise across AWS and Azure, full-stack development knowledge, database expertise, and strong technical leadership.

Run Discovered Labs’ founder-led content operation across LinkedIn and YouTube, from topic selection and editorial development through publication and performance analysis. Responsibilities include shaping founder content, coordinating external partners, repurposing long-form material, improving AI-supported content systems, and using engagement and pipeline data to guide editorial decisions. The role requires strong editorial judgment, hands-on execution, social content expertise, and the ability to work autonomously in an AI-forward, remote environment.

Leads strategy, roadmap, development, and lifecycle management for IoT- and AI-enabled manufacturing products. Partners with engineering, R&D, data science, marketing, sales, customers, and global stakeholders to integrate sensors, actuators, cloud platforms, machine learning, and computer vision. Drives predictive maintenance, quality automation, process optimization, security compliance, market analysis, and customer-centric product improvements.

Annotate and label data accurately according to project guidelines, conduct quality checks, provide feedback on annotation tools and processes, collaborate with project teams, maintain efficiency, and identify issues for resolution. The role requires strong attention to detail, critical thinking, adaptability, communication skills, and comfort with repetitive computer-based work.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Own the AI product strategy and roadmap for HealthEdge’s HealthRules Payer platform. Identify and prioritize AI use cases across claims, member management, enrollment, benefits, and contracts; translate strategy into product requirements; and align product, engineering, data science, UX, marketing, and sales teams. Lead AI governance, regulatory compliance, customer presentations, go-to-market messaging, pilots, and feature commercialization while ensuring responsible AI use in healthcare payer workflows.

Lead long-term technical strategy and execution across multiple teams, architecting and evolving foundational frontend/backend systems and platforms at massive scale. Drive AI/ML adoption, solve ambiguous, high-impact problems, remain hands-on in critical system design and implementation, and align senior leaders on roadmaps and engineering standards.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

Own the design vision and execution for experimental AI-powered learning tools co-created with teachers and researchers. Design teacher- and student-facing products, create flows, wireframes, interaction designs, and functional prototypes, and facilitate collaboration across educators, researchers, engineers, and data scientists. Conduct usability testing and validate research hypotheses while navigating ambiguity, data-heavy workflows, and uncertain AI/ML-enabled features.

Manages science and technology initiatives for sustainable industrial fisheries. Leads multidisciplinary projects involving electronic monitoring, AI, machine learning, computer vision, data systems, hardware, software deployment, and seafood traceability. Oversees vendors, contractors, budgets, procurements, technical assessments, and deployment of systems in remote environments. Translates technical concepts for diverse stakeholders and supports technology evaluation, scaling, and conservation strategy. The role may require domestic and international travel of 25% or more.

Leads enterprise AI enablement and intelligent automation, overseeing use-case intake, prioritization, delivery, governance, adoption, and value realization. Establishes the AI operating model, builds literacy and training programs, manages automation and AIM teams, sets responsible-AI guardrails, tracks adoption metrics, and aligns investment with enterprise transformation priorities. Requires executive stakeholder leadership, portfolio governance, team development, and experience scaling AI or automation capabilities in complex organizations.

Develops, configures, tests, and supports AI solutions, workflows, integrations, and model-enabled applications. Creates technical instructions and documentation, troubleshoots and optimizes AI systems, coordinates technical tasks, and collaborates with architects, delivery leaders, project teams, and stakeholders. Requires a college degree or equivalent, three years of related experience, technical communication skills, and the ability to travel and participate in on-call availability.

Architect and scale cloud-based ML infrastructure supporting large-scale training, massive datasets, model development, and customer services. Own platform design, implementation, deployment, monitoring, reliability, cost optimization, and usability. Collaborate with data science, product, and operations teams, solve complex distributed-systems challenges, and mentor engineers while driving technical innovation.