Top Machine Learning Jobs in Columbus, OH

Designs and deploys AI/ML solutions from prototype through production for government clients. Responsibilities include generative AI using LLMs and RAG, intelligent classification, agentic frameworks, AI coding tools, legacy-system integration, and automated reporting. The role also establishes AI/ML roadmaps, scales adoption, communicates technical concepts to stakeholders, and mentors data scientists.

Lead product marketing for PolyAI's voice assistant products: define messaging and positioning, drive go-to-market strategy and enablement, build competitive intelligence, develop personas and sales collateral, run customer and market research, support revenue enablement, scale and lead the product marketing team, and act as an external spokesperson.

Sell ExtraHops network security analytics to U.S. Federal/Department of War customers by developing territory accounts, engaging senior federal decision-makers, driving new business and renewals, coordinating with resellers and engineers, delivering tailored demos, and executing strategic account plans to meet revenue targets.

Identify and validate AI opportunities across IT operations and cybersecurity, including service management, threat detection, infrastructure monitoring, identity access, endpoint protection, and vulnerability management. Translate operational challenges into structured use cases, assess business value and risk, document data and integration requirements, promote responsible AI, facilitate stakeholder workshops, build internal champions, and monitor emerging AI capabilities while supporting security compliance and change management.

This role leads the ML Acceleration team, focusing on enhancing ML model training efficiency and team management, while driving technical strategy and collaboration.

Owns CareSource’s EDI platform vision, roadmap, backlog, and delivery. Translates healthcare, regulatory, and integration requirements into technical specifications; partners with engineering, architecture, QA, DevOps, trading partners, and business teams; coordinates releases and Agile delivery; monitors transaction performance, defects, SLAs, and platform telemetry; drives data quality, observability, automation, compliance, documentation, and continuous improvement across EDI capabilities.

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.

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.

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.

Design, build, and ship production AI agents integrated end-to-end into a TypeScript/Node.js/React stack. Apply ML judgment to product decisions, improve agent reliability and evaluations, and move quickly in a startup environment owning ambiguous problems.

Lead enterprise AI security architecture, strategy, governance, and secure-by-design implementation across cloud, hybrid infrastructure, software, and AI/ML environments. Design security patterns for LLM hosting, agentic systems, vector databases, and inference endpoints; translate regulatory requirements into technical standards; review complex architectures; implement AI security guardrails and policy enforcement; advise engineering and product teams; and mentor teams while influencing senior stakeholders.

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 definition and evolution of cybersecurity technology platform and service offerings for cyber defenders and CISOs. Drive requirements through software and service lifecycles, deliver differentiated offerings to market, and guide cross-functional teams toward consistent, high-quality execution. The role requires deep expertise in at least two cybersecurity domains, managed services experience, strong communication skills, executive presentation ability, and awareness of AI’s impact on cyber defense.

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.

Transfyr seeks adaptable builders for various roles across CS, biology, and business. Responsibilities include developing sensor stacks, data harmonization, computer vision, machine learning systems, lab operations, project management, and business development.

Manage paid social campaigns and full-funnel strategies across Meta, LinkedIn, TikTok, Pinterest, Snapchat, and other paid channels. Oversee client accounts, analyze performance, identify growth opportunities, build client relationships, and collaborate with SEO, creative, and analytics teams. Contribute to thought leadership, coach associates, maintain quality standards, and explore automation, AI, and LLM search visibility initiatives.

Owns the strategy, packaging, architecture, and delivery methodology for AI testing services. Designs evaluation approaches for LLMs, RAG systems, autonomous agents, and multi-agent architectures using automated graders, LLM judges, and human validation. Supports enterprise discovery, sales, delivery, and technical escalations; advances internal frameworks, develops training datasets and documentation, and defines service offerings, pricing, metrics, and go-to-market content.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Represent statistics on cross-functional teams, oversee programming/CRO work, perform QC, inferential analyses, modeling/simulation, and apply machine learning/deep learning to generate actionable insights. Mentor junior statisticians and support safety, publications, and regulatory responses.

Lead statistical activities for Phase I-IV clinical trials from protocol design through reporting. Represent statistics on cross-functional teams, oversee programmers/CROs, perform QC and inferential analyses using SAS/R, apply statistical, machine learning and deep learning methods for modeling/simulation, and mentor junior statisticians.

Provides strategic and technical leadership for Lilly’s eDiscovery program across the full EDRM lifecycle. Manages legal hold systems, data preservation and collection, processing, review, production, vendor relationships, workflows, and chain-of-custody requirements. Evaluates AI, machine learning, TAR/CAL, predictive coding, and analytics solutions while ensuring defensible legal processes. Partners with Legal, Privacy, Records Management, IT, Compliance, Cybersecurity, outside counsel, and business stakeholders, and mentors team members.

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.