Top Senior Machine Learning Jobs in Columbus, OH

Lead managed services for clients' Azure, Databricks, and Microsoft Fabric data environments. Architect, implement, monitor, troubleshoot, and govern data platforms, ETL pipelines, data warehouses, semantic models, reporting, and AI/ML solutions. Manage incidents and SLAs, advise clients on licensing and technical strategy, communicate solutions, document environments, and mentor distributed engineering teams.

Build and own ClickUp’s AI evaluation systems, agent harness, self-improvement loops, model benchmarking, routing, and fallback strategies. Architect scalable backend and AI platform services for LLM deployment, orchestration, monitoring, logging, and automated evaluation. Improve reliability, privacy, security, and compliance while integrating AI features into the core product and collaborating cross-functionally.

Own company-level strategic initiatives, establish measurable goals, diagnose delivery risks, and recommend resource reallocations. Lead cross-functional transformation focused on go-to-market scalability, annual planning, quarterly reprioritization, monthly business reviews, and AI-enabled operational reporting. Partner with executives and functional leaders to improve the operating model, automate KPI tracking, communicate priorities, and increase organizational velocity.

Own the full enterprise sales cycle for Neuron7.ai’s AI-powered Service Resolution Intelligence platform. Responsibilities include prospecting, executive discovery, strategic account planning, ROI development, technical evaluations, negotiation, procurement, and closing new-logo enterprise deals. The role targets high-tech, manufacturing, and medical device organizations, requiring independent pipeline generation, accurate forecasting, executive relationship management, and collaboration with solution consultants, architects, product, and customer success teams.

Own strategy and execution for a gaming-oriented B2C mobile app focused on advertising, rewards, loyalty, and commerce. Responsibilities include roadmap and backlog management, analytics and A/B testing, conversion optimization, user research, competitive analysis, product documentation, prioritization, and cross-functional collaboration with engineering, design, marketing, legal, operations, and support teams.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Leads the strategy, architecture, implementation, governance, and commercialization of the enterprise data platform. Builds cloud data infrastructure, pipelines, models, DataOps practices, audience intelligence capabilities, and privacy-safe data products. Partners with executive and cross-functional teams to support analytics, personalization, AI, machine learning, reporting, and revenue opportunities. This hands-on technical leader also manages strategic vendors, drives enterprise data initiatives, and communicates technical strategy to non-technical stakeholders.

Provides technical leadership for architecture and evolution of large-scale distributed data platforms supporting Azure network telemetry. Designs streaming and batch systems, establishes reusable engineering patterns, drives cross-team technical strategy, and owns capabilities from design through production operations. Ensures scalability, reliability, security, performance, data quality, and operational excellence while mentoring engineers and influencing technical leaders. The role also involves architectural reviews, dependency management, risk reduction, and applying AI or machine learning approaches to operational systems.

Lead strategic sales of AI Workforce solutions, including Microsoft Copilot, AI agents, Viva, Windows 365, and Azure Virtual Desktop. Develop customer strategies, identify opportunities, build pipeline, conduct consultative business and technical conversations, and orchestrate internal teams and partners to close complex deals. The role requires expertise in technology sales, AI, forecasting, demand generation, stakeholder engagement, competitive positioning, and cross-selling across enterprise and regulated customers.

Leads architecture and production delivery of a near-real-time observability platform for large-scale AI supercomputers. Responsibilities include telemetry ingestion, processing, storage, querying, topology and health modeling, 1P/3P data convergence, AI-assisted anomaly detection, technician dashboards, repair validation, security, reliability, cross-team technical leadership, and mentoring.

Leads advanced analytics, AI, automation, and scientific computing initiatives supporting pharmaceutical clinical development. Translates scientific and business requirements into scalable analytical products, software specifications, decision-support tools, and production automation. Partners across biometrics, clinical development, IT, and business teams; evaluates emerging AI technologies; improves regulated workflows; establishes value metrics; drives adoption and change management; and mentors technical talent.

Leads Payment Integrity strategy and audit optimization by identifying claims-payment anomalies, reimbursement trends, provider behaviors, and new data-mining opportunities. Develops and tests audit concepts, evaluates financial and operational impact, and guides successful concepts through implementation across prepay and postpay processes. Optimizes existing audits, influences cross-functional stakeholders without direct authority, provides executive recommendations, and supports sustainable medical cost savings.

Build and evolve machine learning tooling and infrastructure for AI-powered clinical solutions, including automated prompt tuning, feedback loops, model benchmarking, experimentation, and evaluation. Partner with data science, clinical, software engineering, and product teams to develop scalable solutions, solve ambiguous technical problems, establish engineering standards, and provide technical mentorship without direct management responsibility.

Designs and scales AI-driven security GRC automation, including compliance evidence collection, control testing, risk assessment, audit preparation, and workflow integration. Builds scripts, bots, APIs, and AI/LLM solutions; integrates GRC platforms with security and IT systems; establishes quality controls and guardrails; monitors automation risk and performance; and partners with technical and business stakeholders to improve security compliance maturity.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Leads P&C capital forecasting, target-return and combined-ratio analytics within Enterprise Risk Management. Develops capital monitoring frameworks, evaluates business performance, reviews assumptions, interprets actuarial and financial-risk models, and translates quantitative findings into recommendations for capital deployment. Partners across Finance, Actuarial, Risk, modeling, and business teams while presenting insights to technical and executive audiences. Guides framework design, implementation, governance, and ongoing operation.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own post-sale relationships with referral partners, driving adoption, retention, renewals, expansion, and revenue growth. Serve as a strategic advisor, lead business reviews, resolve escalations, coordinate cross-functional teams, enable product usage, and advocate for partner needs. Maintain partner records and report on satisfaction, renewal, and revenue metrics while developing success strategies and playbooks.

Monitor fraud trends in retail deposit acquisition, analyze large datasets, identify defensive gaps, and develop strategies balancing fraud losses, operational costs, and customer impact. Partner with cross-functional and technical product teams to deliver fraud prevention capabilities, present actionable insights to senior leadership, and support business growth while protecting customers.

Provide legal and regulatory monitoring and analysis for Consumer & Community Banking; draft summaries; manage regulatory and change-management matters; design and improve legal processes; evaluate and apply emerging technologies and AI prompts for legal workflows; respond to regulator, audit, and compliance inquiries; support special research projects and collaborate across teams to solve problems and prioritize work in a fast-paced environment.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Leads talent acquisition strategy for specialized AI, machine learning, robotics, automation, and advanced research roles. Sources and closes highly technical candidates, advises senior leaders on talent markets and compensation, mentors recruiters, builds research and industry relationships, and improves recruiting processes using analytics, recruiting technology, and Lean methods.

Leads end-to-end data architecture, engineering pipelines, semantic-layer development, data quality, monitoring, and platform operations. Manages sprint planning, releases, DevOps metrics, project delivery, and stakeholder communication. Establishes MLOps and machine-learning platform capabilities, mentors data engineers, and ensures reliable, well-documented data solutions that support organizational reporting and analytics needs.

Lead the design and development of Azure Compute Fleet capabilities that orchestrate Virtual Machine Scale Sets across regions. Build distributed control-plane services, APIs, and workflows for capacity placement, scaling, failover, and lifecycle management. Collaborate across Azure engineering teams, drive AI-enabled engineering improvements, participate in on-call operations, and improve reliability, observability, performance, and recovery for hyperscale cloud services.

The AI Engineer designs, develops, and operationalizes responsible AI systems, including generative AI applications, RLHF models, guardrails, prompt engineering, and RAG frameworks. Responsibilities include evaluating and fine-tuning models, developing Python applications on cloud platforms, implementing ML software engineering practices and CI/CD pipelines, and collaborating with stakeholders on AI roadmaps and delivery. The role requires leading complex AI/ML initiatives and translating technical concepts for diverse audiences.