Top Machine Learning Jobs in Louisville, KY

The GTM role focuses on increasing revenue through new sales and partnerships, understanding client needs, and communicating product value.

As a Sr Director Analyst, you will create actionable research in analytics and AI, advise clients, and lead a team in impactful research. Responsibilities include engaging clients, presenting insights, and mentoring team members in analytics & AI best practices.

The Senior Product Manager will lead the integration of machine learning into search relevance, defining product vision and collaborating with teams to enhance ecommerce search functionality.

The Data Science Actuary role involves building and maintaining rating systems and risk models, conducting analysis for underwriting and operations, and integrating new data sources while collaborating with multiple teams.

As Software Engineering Manager, you'll lead a team in enhancing content workflows through automation and AI, develop scalable solutions, and manage cross-functional collaboration.

Serve as the primary technical resource for channel partners to enable partner sales through training, demos, PoV engagements, joint account strategy, and creation of repeatable technical assets and reference architectures. Influence product roadmap via partner feedback and represent 7AI at events to scale partner-led pipeline and long-term customer success.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Lead the Data Sources product roadmap for document parsing, fraud detection, and bank aggregation. Drive metrics (parse accuracy, fraud catch rate, connection success, SLAs), write specs, engage clients, mentor PMs/engineers, and represent the platform externally. Prioritize document types, extraction models, reliability, and scalability to improve conversion, client satisfaction, and operational efficiency across mortgage, tenant screening, and government use cases.

Lead product strategy and roadmap for two flagship B2B SaaS solutions in Food Equipment Services. Drive discovery, prioritize AI-driven quoting and design features, partner with engineering and GTM teams, define success metrics, and oversee delivery, adoption, and continuous improvement.

Lead end-to-end post-sale value stream (implementation through renewal), design the I2R operating model, govern AI/agentic systems, drive retention and time-to-value, partner across Product/Finance/Engineering, apply SAFe and LPM to scale automation and measurable outcomes for adoption, churn reduction, and renewals.

Serve as technical lead in pre-sales for identity verification and fraud prevention. Lead discovery, workshops, POCs, demos, and solution design; advise on risk/compliance; align cross-functionally; influence product; mentor junior consultants and contribute thought leadership.

Own end-to-end client relationships for a book of B2B SaaS customers: drive adoption, engagement, retention, and expansion of AI-powered contract drafting tools. Lead onboarding, training, large-scale rollouts, and translate customer feedback into product improvements while designing scalable CS processes and tracking health metrics to demonstrate value.

This role involves designing, deploying, and maintaining machine learning and AI models in production, managing ML pipelines, and ensuring system reliability and performance.

The AI Developer is responsible for designing and deploying AI solutions, including autonomous agents and predictive models, and integrating them into business operations.

As a Solutions Engineer, you will drive sales growth, support partnerships, and deliver AI-driven solutions while collaborating with various teams.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

AVIA seeks experts in Digital Health and AI for advisory roles to support healthcare systems' technological transformations as part-time, project-based consultants.

The Product Marketing Manager will execute product launches and support go-to-market initiatives, collaborating with cross-functional teams to develop and deliver messaging and enablement materials targeting both technical and business stakeholders.

The Senior Product Manager will lead product initiatives, manage the product lifecycle, and ensure solutions meet customer needs while driving market growth and achieving KPIs.

Lead cross-functional strategic projects, build quantitative models and dashboards to track KPIs, align technical and commercial teams, audit and design scalable operational workflows, and synthesize technical and financial data into leadership-level presentations.

Lead data quality and data management for oncology studies, overseeing DM teams, vendor/CRO management, and compliance with CDISC/ICH-GCP. Develop risk management, integrate and surveil multi-source data, advise stakeholders on data collection and standards, produce metrics and dashboards, manage project resourcing and finances, review contracts, and deliver training to ensure high-quality, regulatory-compliant clinical and real-world data.

Lead development and productionization of large-scale ranking and personalization ML systems. Build data pipelines, features, and models (batch and real-time), collaborate cross-functionally, run experiments, and improve infrastructure for search, recommendation, and marketplace optimization.

Design, build, and productionize large-scale ML models and pipelines for search and recommendations. Collaborate with engineers, product managers, and data scientists to define requirements, develop features, run experiments, and measure impact. Maintain low-latency serving, reproducible training, and scalable data infrastructure for personalization and relevance.

As a Machine Learning Engineer at Shipwell, you'll build and scale AI-powered logistics solutions, maintaining data pipelines and ML infrastructure across the organization.

You will build and own end-to-end ML systems, focusing on training, evaluation, deployment, and integration with applications, while ensuring quality and efficiency.