Top Machine Learning Jobs in Cincinnati, OH

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.

Own and scale Jellyfish’s security engineering program, including strategy, architecture, secure SDLC governance, AI security, threat modeling, vulnerability remediation, incident response, penetration testing, and bug bounty programs. The role combines hands-on software development with executive advising, cross-functional leadership, mentorship, and security risk management across SaaS infrastructure and customer-facing AI products.

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 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.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Develops scalable AI and machine learning solutions for client use cases, including model development, data analysis, production deployment, conversational AI, and multi-agent architectures. Collaborates with stakeholders on system rollouts, specifications, testing, maintenance, and issue management. Requires experience with machine learning, deep learning or NLP, cloud-based AI/ML services, and conversational AI orchestration. Travel may range from none to 100% based on business needs.

Designs, builds, and scales enterprise AI applications using classical machine learning, generative AI, RAG, and agentic architectures. Develops intelligent workflows, autonomous agents, knowledge systems, chatbots, copilots, and decision-support solutions integrated with enterprise platforms and APIs. Leads AI governance, evaluation, observability, security, and human-in-the-loop controls while advising clients on enterprise AI transformation. Requires extensive experience with Claude, OpenAI, LLMs, cloud platforms, vector databases, semantic search, and production-grade AI implementations.

Own the AI product strategy, backlog, roadmap, discovery, requirements, and delivery for Quinn, a platform supporting SEC disclosure workflows. Partner with customers, engineering, legal, security, and sales to define trusted AI capabilities, evaluation frameworks, quality standards, governance practices, pilot programs, and release priorities. Translate customer and market insights into validated solutions while balancing technical feasibility, regulatory requirements, security, privacy, and business objectives.

Leads strategy, performance, transformation, and financial results for a 24/7 corporate travel service operation supporting voice, chat, text, and email. Oversees 70+ employees and operational leaders across domestic, international, VIP, after-hours, fulfillment, and group travel teams. Drives workforce planning, service quality, automation, AI adoption, business continuity, budgeting, client retention, supplier collaboration, and talent development while maintaining privacy, security, compliance, and human oversight.

Leads the Streaming Test Analytics team across five sites, overseeing AI-driven analytics, anomaly detection, software infrastructure, test data management, governance, and process simplification. Drives customer adoption, program execution, stakeholder alignment, employee development, recruiting, and operational handoffs. Requires technical leadership in machine learning, aircraft engine performance, Python or Java development, Agile CI/CD, and large-scale program management.

Owns end-to-end delivery of enterprise AI projects from technical scoping through deployment. Coordinates engineering, data science, and business teams; manages timelines, budgets, resources, risks, and project KPIs. Ensures AI initiatives address regulatory compliance and data privacy requirements, facilitates communication between technical and business stakeholders, and supports successful operational handoffs.

The GRC Analyst manages third-party risk assessments, vendor due diligence, security policies, risk analysis, internal audits, and SOC 2 audit support. The role involves maintaining the GRC program, tracking findings, coordinating stakeholders, promoting security awareness, and using AI and machine learning to automate compliance processes. Candidates should have 1–2+ years of relevant experience, strong communication skills, and familiarity with risk methodologies, vendor assessments, policies, and compliance audits.

Develop and support software, automation tools, dashboards, and alarms for cloud infrastructure, cost attribution, and cloud efficiency. Collaborate with cross-functional teams and senior engineers to design reliable systems, APIs, databases, tests, and AI agents. Contribute to architecture and automation strategies while maintaining strong security, communication, and delivery practices.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Supervises an application engineering team responsible for designing, developing, integrating, testing, deploying, and maintaining software applications supporting insurance processes. Oversees daily workflow, technical priorities, performance optimization, infrastructure alignment, user support, process improvements, and stakeholder collaboration. Provides coaching, mentorship, and technical expertise across programming languages, cloud platforms, development frameworks, and machine learning concepts while managing performance and budget targets.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Leads the strategy, technical direction, and delivery of insurance data science across pricing, underwriting, cost modeling, demand modeling, and growth. Oversees predictive modeling standards, model lifecycle governance, engineering collaboration, regulatory alignment, and production deployment. Builds and develops a high-performing data science organization while partnering with actuarial, product, underwriting, pricing, and executive leadership to connect analytical work with profitability and business outcomes.

Leads control management for JPMorganChase’s Consumer and Community Banking Operations portfolio. Designs and strengthens risk and control frameworks, identifies emerging compliance and operational risks, drives governance and issue management, and promotes consistent agile control practices. Partners with Product, Technology, Legal, Compliance, Audit, and Risk stakeholders to support transformation initiatives, regulatory compliance, control effectiveness, and operational resilience. Requires strong risk-based decision-making, change management, stakeholder influence, executive communication, and data literacy.

Leads commercial analytics and business intelligence strategy, including executive dashboards, account reporting, revenue and pricing analytics, operational KPIs, forecasting, segmentation, and predictive modeling. Partners with Sales, Finance, Marketing, Operations, and Product to improve revenue, profitability, customer retention, and marketplace performance. Presents insights to executives and customers while managing analytics teams, budgets, vendors, and BI scalability.

Analyze large datasets, identify meaningful patterns, develop machine learning models, and deliver actionable insights for business decisions. Collaborate with cross-functional teams to understand data needs, communicate findings clearly to stakeholders, and stay current with advances in data science and AI technologies.

Performs advanced data and statistical analysis on structured and unstructured data, develops predictive models and machine learning algorithms, and delivers actionable insights for business growth. Builds data sets, designs experiments, conducts reporting, and translates business needs into measurable analytical solutions. Partners with stakeholders to communicate findings and drive informed banking decisions while managing risk and supporting assigned project planning.

Own the technical side of deal progression for airline deployments: qualify opportunities, run demos and POCs, author integration and deployment architectures (PSS, APIs, data feeds, DNS, identity, networking), respond to RFPs/security questionnaires, scope SOWs and NFRs, and build reusable demo/reference assets to drive adoption and expansion while liaising between sales, engineering, and customers.

Leads the architecture, development, and deployment of enterprise-scale AI systems and platforms. Establishes technical direction, governance, architecture standards, and responsible AI practices while modernizing legacy systems through code transformation and service decomposition. Develops AI-enabled SDLC practices, partners with engineering teams to drive adoption, and provides technical leadership and mentorship across software engineering, distributed systems, cloud, APIs, microservices, and DevOps.

Provides bioinformatics consultation, computational analysis, statistical support, and production pipeline development for HIV-related genomic and clinical research at NIAID. Responsibilities include sequence and gene expression analysis, variant calling, genome assembly, comparative genomics, proteomics, and epigenomic workflows. The role supports scientific programming, experimental design, data dissemination, scalable research resources, and publications. Candidates need expertise in programming, workflow frameworks, containerization, high-performance computing, and next-generation sequencing, with HIV research experience preferred.

Lead go-to-market strategy for Sprout Social’s AI portfolio, including the Trellis AI agent. Develop enterprise launch playbooks, positioning, executive messaging, campaigns, and enablement programs. Analyze market and competitive dynamics, influence product roadmaps, improve launch processes, and partner with Product, Sales, Revenue, Brand, and executive leadership to drive adoption, revenue growth, deal expansion, and category leadership. The role also mentors marketing team members and operates with substantial autonomy.