Top Senior Machine Learning Jobs in Cincinnati, OH

The role involves delivering technical solutions, integrating AI/ML models, developing software, and mentoring junior engineers while ensuring customer satisfaction through engagement and solution design.

The Lead Data Scientist will architect AI solutions for the energy sector, develop ML algorithms, and collaborate with leadership to shape product strategy.

Lead complex projects leveraging AI and machine learning to deliver innovative data-driven solutions, requiring extensive experience and technical expertise.

Lead efforts in applying reinforcement learning techniques to enhance model quality and controllability for creative applications. Mentor researchers and contribute to human-in-the-loop systems.

Lead the Mid-Market Sales team to connect technical organizations with AI and data science tools, driving adoption and growth through value-based selling and strong partnerships with engineering teams.

As a Product Manager for Risk, you'll design fraud prevention tools, manage cross-functional teams, and improve fraud detection methods.

As a Staff Software Engineer, you will lead engineering teams, collaborate cross-functionally, drive technical initiatives, and contribute to code while ensuring system resiliency.

The AI Engineer will design, implement, and prototype GenAI and ML solutions to enhance operational intelligence and efficiency in investment services.

The Senior Engineering Manager at Planet leads the engineering team, focusing on delivering products for Defense Intelligence. Responsibilities include mentoring engineers, refining processes, and collaborating across teams for effective deployment of technology.

The VP of Marketing will scale marketing functions, drive demand generation, build teams, establish marketing strategies, and coordinate with sales to enhance pipeline and revenue growth.

Lead product development for credit card decisioning and customer journeys, translating credit policy and data into real-time actions. Partner with Engineering, Data, and Credit to operationalize underwriting and payment models, run experiments, use SQL for analytics, and craft roadmaps that balance business outcomes with customer well-being.

Lead the development of intelligent decision engines modeling customer intent in real-time using advanced data science techniques such as causal inference and machine learning. Collaborate with cross-functional teams to optimize systems for search, fulfillment, and customer experience.

Lead technical engagement across pre-sales, deployment, and post-sales for on-premises quantum systems. Drive customer success, inform product development, support sales with deep HPC/AI/optimization expertise, present at industry events, and translate customer needs into deployment strategies and R&D feedback.

As a ML Engineer focused on inference, you'll design and optimize deep learning models for real-time communication AI applications, collaborating with cross-functional teams and ensuring production readiness.

Design and maintain scalable machine learning infrastructure, collaborating with data scientists, ensuring performance, security, and compliance of AI systems.

As an AI/ML Ops Engineer, you will architect and operate ML pipelines, automate CI/CD processes, and collaborate with cross-functional teams to enhance engineering productivity.

The role involves deploying, optimizing, and maintaining ML-driven motion planning and control algorithms for autonomous driving, collaborating across teams to ensure reliability under performance and safety constraints.

Serve as the presales technical expert for ML capabilities: lead discovery, architect ML solutions, run demos/workshops/proofs-of-concept, coordinate cross-functional teams, and inform product direction based on customer feedback.

Design, architect, and deploy generative AI/LLM solutions from prototype to production; work directly with clients to translate business needs into technical plans; write production-quality code integrating LLMs and ML models; collaborate with cloud, DevOps, and frontend teams; support proposals, sales, and evaluation/observability of models.

The Senior Backend Data Engineer will extend data ingestion and processing pipelines, build APIs and backend services, and provide technical leadership.

The Senior Machine Learning Engineer at Grailed will enhance personalization and recommendations, develop AI/ML solutions, and collaborate across departments for data-driven insights.

Lead Yahoo's Data Activation product area: define vision and strategy, partner with Data Science and Engineering, drive cross-vertical data activation initiatives, deliver measurable business impact, and mentor/manage product teams to execute on audience, personalization, and targeting use cases.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

The Director of Machine Learning Science will lead teams in delivering ML solutions, drive innovation in search and personalization, and engage with engineering and product teams.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.