Top Machine Learning Jobs in Louisville, KY

Own discovery, definition, and delivery of marketplace directory features for Avetta’s B2B SaaS platform. Serve as the customer advocate, conduct research and usability testing, analyze product metrics, prioritize problems, define KPIs, and collaborate with engineering, UX, marketing, and customer success. The role focuses on scalable marketplace and platform products involving search, profiles, matching, recommendations, onboarding, monetization, trusted data, and network effects.

Reviews and refines AI-generated content and data outputs, develops prompts, evaluates model performance using rubrics, conducts independent research and fact-checking, annotates data, and summarizes complex findings in technical reports. Works asynchronously with project leads and domain experts to improve AI output quality and analytical standards.

Own and modernize Apartment List’s B2C lifecycle marketing program across email, push, and SMS. Build segmentation, personalization, partnerships, cross-sell, forecasting, experimentation, and measurement systems. Lead analytics, attribution, deliverability, and revenue optimization while remaining hands-on with journeys, templates, dynamic content, audience logic, SQL, and troubleshooting. Manage a two-person team, partner cross-functionally on roadmap priorities, and oversee the Iterable relationship.

Own strategic enterprise accounts across expansion and new-logo sales motions. Build executive relationships, develop account plans, run account-based outbound, navigate complex buying committees, deliver consultative demonstrations, negotiate contracts, and close high-value SaaS deals. Partner with Customer Success, Business Development, and Marketing while maintaining Salesforce pipeline and forecasts. Success requires consistently meeting quota through longer-cycle, multi-stakeholder deals and contributing to the evolving enterprise sales playbook.

Drive new-account acquisition and cloud migrations for AI and infrastructure solutions. Generate pipeline through global outbound prospecting, execute multichannel outreach, manage the full enterprise sales cycle, and close large cloud, infrastructure, and data center deals. The role requires deep knowledge of AI computing, cloud infrastructure, power capacity, cooling systems, financial modeling, and B2B enterprise net-new cloud sales. Candidates work from Akamai’s San Francisco office and collaborate across time zones.

The AI/ML Data Contributor will perform data labeling, annotation, and evaluation for machine learning projects, following guidelines and completing tasks on time.

As an AI/ML Data Contributor, you'll perform data labeling, content evaluation, and user testing to improve machine learning models while participating in various projects.

Own technical product marketing for Bloomreach’s APIs, integrations, and agentic AI platform. Translate platform capabilities into positioning, use cases, partner launch strategies, customer storylines, sales enablement, and go-to-market materials. Collaborate with Product, Engineering, Solutions Engineering, partners, sales, and technical buyers. Define launch metrics, coordinate milestones, communicate product value, and evaluate post-launch results.

Design and deploy machine learning models for financial document processing, optimize large language models, collaborate with cross-functional teams, and guide junior peers in a fast-paced environment.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

Leads Stitch Fix’s Product Algorithms portfolio across Growth, Styling, and Fix & Freestyle. Defines strategy and roadmaps for machine learning, AI, experimentation, personalization, and product analytics; drives scalable production capabilities and measurable business outcomes; improves planning, operational readiness, incident management, and decision-making; and builds a high-performing organization of managers and senior technical contributors while partnering with executive and cross-functional stakeholders.

Own the strategy, requirements, evaluation, and execution of AI agent products and systems. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define evaluation frameworks, drive prioritization, and ensure AI features are understandable, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions and reliable real-world workflows.

Own the strategy, requirements, evaluation, and reliability of AI agent products. Partner closely with ML, backend, and mobile engineers to make trade-offs across quality, latency, cost, reliability, and user experience. Define offline and online evaluation frameworks, drive product execution, and ensure AI features are correct, predictable, safe, and trusted. Translate model capabilities and feedback into product decisions, roadmaps, and rapid iteration.

The Senior Product Architect will design security products, collaborating with product management and engineering teams, focusing on architecture and functionality for high-level product features.

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 enterprise AI and transformation engagements—own customer relationships, scope buildable solutions with FDE, drive commercial outcomes and expansion, advise C-suite on AI strategy, and create repeatable, scalable offerings to evolve Tive into an AI-powered intelligence platform.

Develop reusable ML tooling and libraries, collaborate with data scientists to productionize models, build services and APIs (Docker/Linux), follow engineering best practices, and support project lifecycle from intake to maintenance.

You will execute and improve insurance workflows, analyze operational efficiency, collaborate with product teams, and support onboarding and documentation efforts.

Lead end-to-end ML systems for identity verification, including document authenticity, face match, liveness and deepfake detection. Build GNN-based identity graphs, behavioral/device-intelligence models, vendor benchmarking/evaluation, and production enforcement. Mentor engineers and align ML architecture with Product, Compliance, Risk, and Security stakeholders.

Review, label, and QA datasets for AI/ML training; maintain trackers, databases, and dashboards; follow annotation guidelines and SOPs; prepare and clean data; document processes; collaborate to resolve data queries while ensuring confidentiality and timely delivery.

Build and deploy production-grade LLM applications, AI agents, models, and scalable RAG pipelines for investment and business workflows. Architect secure MCP integrations with enterprise systems, establish MLOps and LLMOps practices, optimize model performance and latency, and develop evaluation, monitoring, governance, and rollback processes. Collaborate with data engineering and platform teams to provide secure, governed access to organizational data.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

The role involves conducting research and optimizing machine learning systems while collaborating with technical staff to enhance product performance.

Lead development of safety frameworks and V&V for end-to-end autonomous robotics, perform risk assessments and safety reviews, derive technical safety requirements, and coordinate cross-functional teams to monitor fleet performance and deploy scalable autonomy.

As a Research/ML Engineer, you will translate cutting-edge AI research into product solutions, develop safety and reliability systems, and collaborate with technical teams.