Top Senior Machine Learning Jobs in Baton Rouge, LA

Lead and mentor engineering teams while owning platform architecture (React, Node/Express, Postgres, AWS). Drive TypeScript migration, design ETL and AI/LLM integration frameworks, ensure reliability and observability, manage delivery, incidents, and hiring, and define technical strategy for production ML/AI systems.

Lead design, development, and production deployment of ML models and GenAI/LLM solutions to optimize clinical trial workflows. Build scalable pipelines, monitoring, and CI/CD for robust production use. Collaborate cross-functionally, mentor junior engineers, and communicate technical results to technical and non-technical stakeholders.

Lead end-to-end supply chain transformation engagements, advising executives and directing multidisciplinary teams to improve planning, procurement, logistics, inventory, and supplier performance. Design future-state architectures, build business cases, drive implementation, grow client relationships, and scale practice capabilities while delivering measurable operational and financial impact.

Lead end-to-end supply chain transformation engagements for commercial and utility clients. Advise executives, design future-state supply chain architectures, oversee implementation across planning, procurement, logistics, and analytics, build financial value cases, and manage multidisciplinary teams to deliver measurable operational and financial results.

Design, build, and deliver end-to-end AI applications for customers, spanning data ingestion, model training (classical and generative), deployment, API and infrastructure architecture, MLOps, monitoring, and stakeholder communication. Translate business problems to technical solutions, drive measurable outcomes, mentor customer teams, and ensure production reliability and cost optimization.

Lead delivery of LLM/AI-enabled systems: define LLM selection, prompt engineering, RAG/vector DB and knowledgebase design, AI agents, guardrails, evaluation frameworks, observability, latency and cost management. Manage offshore engineering team, run sprints, unblock delivery, and report status to leadership.

The Senior Principal Product Manager will lead Rockerbox's measurement and modeling products, ensuring accurate methodologies and partnering with Data Science and Engineering to drive product strategy and execution.

Lead machine learning initiatives, oversee product development, improve execution pace, enhance team reliability, and foster team growth at Hightouch.

Lead vision, strategy, and roadmap for data products powering catalog, taxonomy, recommendations, ads, and AI/ML systems. Partner with data engineering to build data platform, governance, identifiers, and quality metrics. Ship data-driven experiences for retailers, partners, and internal teams and translate data quality into measurable business outcomes.

Lead product vision and roadmaps across multiple initiatives for Sift's fraud-prevention platform. Partner with engineering, data science, sales, and marketing to define requirements, write specs, run customer discovery and beta programs, and drive go-to-market and adoption. Balance technical execution with strategic portfolio-level product strategy.

Lead architecture, design, development, deployment, and optimization of an agentic AI platform. Partner with product, data, security, and business teams to productionize AI solutions, establish engineering best practices, mentor teams, and drive reusable AI services, automation, and operational improvements to deliver business impact.

The Senior Data Engineer will own the data strategy, managing sourcing, structuring, and optimizing multimodal data to enhance AI models and products.

As a Senior Software Engineer, you'll build and operate the ML platform, optimizing data operations, managing the feature store, and supporting ML initiatives while driving architectural roadmap decisions.

The Staff Engineer will architect and build AI and ML infrastructures, mentor engineers, and lead high-impact initiatives to enhance ML capabilities across Attentive's platform.

The Machine Learning Solutions Architect designs and implements data solutions, overseeing model deployment and ensuring robust performance and integration within customer environments.

Lead development and deployment of predictive and ML models for credit risk, collections, and operations. Mentor data scientists, promote MLOps and modern tools, present insights to stakeholders, and drive experimentation with techniques such as causal inference and GenAI.

Design, develop, implement, and monitor statistical and machine learning models to support credit risk, collections, servicing, marketing, and forecasting. Build data pipelines, translate business needs into analytical solutions, support model governance, testing, deployment, and ongoing performance monitoring, and communicate results to stakeholders.

Own Cash Application and Deduction Resolution Management products end-to-end. Lead discovery, define requirements, prioritize roadmap, partner with engineering/design/sales, ensure financial accuracy, build ERP integrations, drive launches, and maintain product quality and customer-focused outcomes.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

The Senior Data Scientist will develop scalable ML models, analyze large datasets for insights, and collaborate with teams to enhance business performance through data-driven solutions.

The Senior Machine Learning Engineer will build and optimize ML systems for CRM marketing, collaborating with cross-functional teams to impact customer engagement and product functionality.

Lead vision, strategy, and roadmap for pricing platforms, owning internal Rating Plan Manager and tooling to speed model deployment, improve workflow reliability and observability, enable self-service experimentation, and support regulatory/state-level pricing needs through cross-functional collaboration.

Design, develop, and deploy causal inference and predictive models (uplift, synthetic control, DML) for customer loyalty, churn, and LTV. Build foundational data models and scalable features, perform large-scale SQL ETL, operationalize models in cloud, partner with stakeholders, and present insights to drive revenue and loyalty program optimization.

Partner with customers to design and deliver production-ready AI/ML solutions, drive POC-to-production success, troubleshoot technical issues, inform product roadmap with customer feedback, and communicate outcomes to stakeholders.