Top Remote Machine Learning Jobs in Columbus, OH

Own and develop SandboxAQ’s intellectual property function, including patent portfolio strategy, invention harvesting, prosecution, lifecycle management, outside counsel oversight, freedom-to-operate analyses, trademark clearance, and trade secret programs. Partner with scientists, engineers, and business teams to protect innovations, inform product strategy, support transactions, and build scalable IP processes in a fast-growing AI-focused company.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

Leads and scales the post-sale customer success organization, overseeing customer retention, expansion, adoption, renewals, and customer outcomes. Manages 20 or more Customer Success Managers and Leads, develops scalable lifecycle processes, integrates AI into customer success operations, and partners cross-functionally on product and revenue strategy. The role also manages strategic accounts, international expansion across Mexico and Latin America, team development, performance metrics, customer advocacy, and operational excellence.

Supports responsible AI governance across the AI lifecycle by maintaining use case and model inventories, risk assessments, model cards, control evidence, audit documentation, transparency records, and remediation tracking. Translates regulatory and policy requirements into practical processes, coordinates cross-functional reviews, evaluates AI risks and controls, and communicates technical governance information to legal, compliance, audit, business, and executive stakeholders.

Manage paid media strategies and campaigns across search, social, display, and programmatic channels. Advise clients using integrated paid, organic, and analytics data; oversee campaign performance, keyword research, ad copy, landing page recommendations, and presentations. Build client relationships, mentor account associates, collaborate with SEO and data teams, and use AI to improve workflows and outcomes.

Develop and lead paid media strategies across search, social, display, and programmatic channels. Manage campaign strategy, performance analysis, testing, optimization, and integrated paid and organic recommendations. Consult with clients, present results, build relationships, mentor account associates, and identify data-driven growth opportunities. Use AI tools to improve workflows and contribute insights across the team.

Lead strategy to define, measure, and evolve Solution Engineer and Cloud Solution Architect excellence for Microsoft Security. Use data, AI-powered analytics, and customer insights to identify performance drivers, design capability strategies, advise senior leaders, and drive field transformation. Build governance, risk remediation, and scalable enablement programs while partnering across engineering, product, sales, and enablement to measure impact and continuously improve outcomes.

Design, build, and deploy production-ready intelligent solutions using machine learning, deep learning, generative AI, and large language models. Develop RAG pipelines, integrate AI services, manage model deployment and MLOps workflows, and apply strong software engineering practices. Collaborate with engineering, product, and data teams in a distributed environment to create scalable, reliable, responsible AI-powered products.

Designs statistical analysis plans and validates machine learning models using rigorous performance, calibration, uncertainty, subgroup, fairness, and longitudinal analyses. Applies biostatistical methods to healthcare data, documents assumptions and limitations for auditability and regulatory readiness, and translates complex findings into clinically meaningful insights. Collaborates with engineering, machine learning, data, clinical, and product teams.

Leads technical strategy and product adoption for major Retail and CPG enterprise accounts as Databricks’ primary technical voice. Partners with account executives, guides customers through data and AI transformations, builds technical champions, aligns solutions to business strategies, and mentors team members. Requires extensive pre-sales, big data, cloud, data science, programming, and production data systems experience.

Designs, integrates, tests, maintains, and upgrades complex IT systems across hardware, software, and security domains. The role validates system compliance, diagnoses issues, recommends improvements, and supports secure, reliable mission-critical environments. Responsibilities also include working with unstructured data using open-source tools, cloud computing, machine learning, and data visualization technologies, while collaborating with cybersecurity teams.

Leads the See & Scout engineering organization across software, data, machine learning, and robotics. Owns technical strategy, architecture, and multi-year roadmaps for scalable cloud, distributed data, edge, and machine learning platforms. Oversees the full data and ML lifecycle, production delivery, operational excellence, and customer-focused agricultural intelligence capabilities. Recruits and develops engineering leaders, partners cross-functionally, and aligns stakeholders across Blue River and John Deere.

Build and lead Nebius’s federal affairs function in Washington, D.C. Develop policy strategy across AI regulation, trade, energy, infrastructure, and national security; establish bipartisan relationships with Congress and executive agencies; represent the company in federal initiatives and coalitions; assess regulatory risks; coordinate with legal, communications, and infrastructure teams; manage outside lobbying partners; and hire staff as the function scales.

Develop and test AI software using large datasets, algorithms, and statistical analysis for industrial applications. Collaborate with machine learning and data engineers to build integrated AI/ML solutions, evaluate performance, monitor industry trends and regulations, and present progress to leadership and stakeholders. The internship offers hands-on experience, mentorship, and exposure to practical AI innovation.

Develop and test AI software for industrial applications using Python, JavaScript, and C++. Evaluate data, statistics, and algorithms; collaborate with machine learning and data engineers; support end-to-end AI/ML integration; monitor industry trends and regulations; and present progress to leadership and stakeholders.

Lead research, architecture, and production deployment of large-scale algorithms for budget pacing, bid optimization, and marketplace balancing in Yahoo’s DSP. Apply control theory, optimization, and machine learning to real-time systems, while establishing AI-augmented research and engineering workflows. Own multi-quarter initiatives, define evaluation frameworks, guide technical strategy, collaborate with product and engineering leadership, mentor scientists and engineers, and communicate complex research and architectural decisions to executives.

Lead the vision, strategy, roadmap, backlog, delivery, adoption, and lifecycle management of an enterprise AI platform. Manage three direct reports and collaborate across technology, cybersecurity, risk, legal, compliance, data, and analytics. Ensure secure, scalable, governed, and responsible AI capabilities while translating business and technical priorities into measurable product outcomes. Drive stakeholder alignment, platform adoption, continuous improvement, executive communication, and team development in a highly regulated environment.

Leads Magellan Health’s enterprise data and analytics strategy, modernization, engineering, governance, business intelligence, and AI/ML enablement. Oversees data platforms, pipelines, quality, lineage, compliance, and reporting while partnering with clinical, operational, and financial stakeholders. Builds and develops a 30+ person organization, manages a $3M–$5M budget, oversees vendors, and presents investment cases to executive leadership. Drives transformation from a low-maturity environment to a governed, insight-driven enterprise data platform.

Leads and manages an applied machine learning team developing fraud detection and identity verification models. Responsibilities include people management, coaching, code review, production ML systems, model lifecycle ownership, experimentation, deployment, monitoring, fraud research, cross-functional prioritization, and communicating results. The role remains hands-on while partnering with Product, Engineering, Risk, and leadership to drive measurable business impact and shape future product strategy using machine learning and AI.

Leads an applied machine learning team and owns fraud detection and identity model strategy, development, deployment, monitoring, and iteration. Partners with Product, Engineering, Risk, and senior leadership to set priorities and deliver business impact. Provides technical mentorship, reviews code, guides modeling and architecture decisions, researches fraud patterns, develops ML capabilities, and shapes responsible AI use under data governance and security constraints.

Operate and improve enterprise AI/ML platforms across Palantir Foundry, AWS Bedrock, and Amazon SageMaker. Responsibilities include deployment, monitoring, observability, automation, governance, model lifecycle management, incident response, root cause analysis, CI/CD, infrastructure as code, and production reliability. The role provides technical leadership and mentorship while partnering with data, infrastructure, security, architecture, product, and engineering teams to support cloud-based AI workloads and Generative AI adoption.

Lead the strategy, design, deployment, and scale-up of AI-powered health products across the Global South. Own product roadmaps, execution, government-system integration, stakeholder adoption, partnerships, grant development, and portfolio expansion. Collaborate with engineering, machine learning, program, and domain teams to deliver sustainable, measurable public-health impact.

Participants are needed for an AI technology research study, offering compensation up to $600 for ~1.5-2 hours of participation over one week, requiring skills in tech-related roles.

Performs advanced physical and remote insurance premium audits for business clients. Reviews business records, interviews owners and managers, investigates exposures, documents findings, prepares written audit reports, schedules assignments, communicates results, and submits completed work for quality review. The auditor must manage deadlines independently, correct returned audits, maintain accurate records, and use Microsoft Office applications. This remote role requires reliable transportation, a valid driver’s license, strong analytical and communication skills, and at least five years of premium insurance auditing experience.