Top Remote Machine Learning Jobs in New Orleans, LA

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.

Own the research-to-production pipeline: harden training/evaluation workflows, build packaging/deployment tooling, design release gates, optimize inference and serving for latency/throughput, establish benchmarking and validation, and instrument feedback from production to accelerate research iteration.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Develop ML/RL models and infrastructure for AV simulations, optimize training loops, and support project timelines in autonomous vehicle tech.

Own and scale Root's largest enterprise partnerships (OEMs, financial institutions, dealer groups). Drive account strategy, manage a $100M+ pipeline, identify and close new business, lead executive negotiations and contract execution, coordinate cross-functional launches, monitor partnership health, and influence product and commercial strategy to deliver growth.

Serve as the primary product contact embedded with health system clients to discover workflows, design AI-powered solutions, scope pilots, and lead 0→1 deployments. Translate clinical and administrative workflows into product requirements, drive UAT and go-live, measure business success metrics, and surface field insights into the product roadmap. Travel to client sites for discovery and deployment support and collaborate with ML engineers, FDEs, and solution teams to ensure measurable ROI and expansion.

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.

Lead development and integration of predictive pricing models for home insurance, modernize state rating plans, support rate filings, monitor performance and recommend pricing actions, analyze competitor strategies, develop pricing for expansion, build internal pricing analytics software, and coach/mentor analysts.

OneSix is seeking motivated professionals for future opportunities in data and AI consultancy. Interested candidates should submit their resumes to stay in touch.

Lead strategy and roadmap for DTNs upstream intelligence portfolio, especially Farm Intelligence. Conduct customer discovery, define product metrics, prioritize features, and partner with Engineering, Design, Data Science, and Commercial teams to deliver data-intensive, AI-enabled B2B SaaS products. Drive launches, adoption, and continuous optimization through experimentation, analytics, and stakeholder alignment.

Lead operationalization of AI strategy by implementing scalable AI platforms, standards, and governance. Identify and prioritize high-impact AI and analytics use cases, drive end-to-end delivery into production, embed AI into business processes, manage AI teams, mentor practitioners, and evaluate emerging AI/GenAI technologies to ensure responsible, secure, and measurable business impact.

Lead translation of Global Partner Program strategy into operational, scalable programs. Build and run partner lifecycle frameworks, governance, reporting, and AI-driven insights. Manage day-to-day program operations, roadmaps, KPIs, executive reporting, cross-functional coordination, and partner enablement to drive partner growth and commercial outcomes.

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.

Research, draft, edit, and validate practitioner-facing US federal tax articles using AI tools. Ensure accuracy and currency, collaborate with data scientists, and align content with tax firm workflows and customer needs while helping build the content function.

Senior product leader setting the multi-year Applied Intelligence vision and roadmap for AI-powered B2B AR products. Own end-to-end AI product lifecycle, governance, evaluation standards, talent building, cross-functional partnership, and external representation to drive commercial impact and customer adoption.

The Senior AI Engineer at RegScale designs and operates AI systems, ensuring reliability and performance while overseeing the data pipeline and compliance integration, alongside improving AI capabilities across the engineering organization.

Design and run partner presales enablement programs that build hands-on technical proficiency across ISV and C&SI partners. Own curriculum, assessments, roadmaps, KPIs, and large-scale learning events; coach trainers; align cross-functionally to drive partner-sourced pipeline and certification outcomes.

Lead data science for Root's digital partnerships channel, managing a team to drive growth, profitability, experimentation, forecasting, optimization, and measurement. Partner with cross-functional teams to improve acquisition economics, influence product and technical roadmaps, deliver executive reporting, and establish scalable operating processes.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.

Design, implement, and optimize AI-powered solutions to support financial compliance and controls. Monitor GAAP/IFRS adherence, automate controls and reporting, support internal/external audits, and manage complex accounting areas like revenue recognition and lease accounting while collaborating with finance, audit, and technology teams.

Drive data-informed capital allocation by building financial models (NPV, IRR), applying AI/ML for forecasting and scenario planning, creating build-vs-buy and prioritization frameworks, implementing decision-support systems, collaborating with cross-functional stakeholders, and monitoring post-investment performance to refine allocation models.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

The Customer Success Engineer will lead deployments, serve as a technical advisor, and support customer engagement, focusing on product enhancements and user experience.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

Lead pre-sales technical engagements for Conversational and Generative AI solutions, collaborate across teams, and design value-driven demos for enterprise customers.