Top Remote Machine Learning Jobs in Atlanta, GA

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

The Principal Architect will lead AI/ML solutions, mentor teams, and collaborate with clients to design and deliver scalable systems using Google Cloud technologies, ensuring compliance with ethical standards.

The Senior Vice President of Underwriting will oversee underwriting outcomes across multiple lines, driving growth and improving loss ratios through data-driven strategies and leadership.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The role focuses on leading editorial efforts to define industry narratives around energy infrastructure, translating regulatory changes into strategic content for executives, and influencing sales and positioning through high-impact communications.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

The AI Executive Partner will advise C-Suite executives on leveraging AI to drive business outcomes, manage member relationships, and deliver innovative AI solutions.

The Senior Director leads research in Application Platforms & AI, guiding clients in AI strategy and market trends, while producing critical research content and engaging with clients directly.

The Senior Display Media Account Manager develops and executes digital media strategies, focusing primarily on Amazon DSP, while fostering client relationships, providing analytics, and driving business growth for clients.

As a P&C Actuary, you will assess insurance risks, review regulatory compliance, support audit teams, and document findings while nurturing client relationships and contributing to practice development efforts.

The Senior Vice President, Data Science & Analytics will lead analytics and data science functions, drive innovation, implement AI, and oversee data strategies across financial services.

Lead product strategy and roadmap for a unified data platform, spanning ingestion, modeling, and an intelligence layer. Partner with engineering and data science to deliver cloud-native pipelines, curated analytic models, and ML productization. Drive governance, metrics, cross-functional alignment, backlog management, and Agile practices to maximize platform value for internal teams and clients.

Manage a portfolio of SaaS customers, build relationships, monitor usage, prevent churn, handle support and troubleshooting, identify upsell/renewal opportunities, and relay customer feedback to product and engineering.

Senior product engineer owning end-to-end product surfaces for a computer vision platform. Ship features from idea to production, prioritize roadmap, design UX details, integrate APIs, improve annotation and model-assisted labeling, and collaborate with engineering and users to drive product impact.

Support AI training initiatives by developing and refining financial models, translating market research and due diligence into structured AI training datasets, and partnering with stakeholders to convert complex financial concepts into training inputs. Evaluate and improve AI-generated financial analyses, identify gaps in modeling or valuation assumptions, and contribute strategic insights to enhance AI-powered private equity tools in a fully remote environment.

Create and curate high-quality graphic design datasets and training materials for AI systems. Collaborate with engineers to evaluate and refine AI-generated visuals, document design processes and style guides, and translate design concepts into actionable training data. Stay current with design trends and communicate feedback to cross-functional 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.

Remote neurologist AI trainer who annotates and reviews clinical data, guides ML model training, interprets neurological diagnostics (EEG, EMG, LP), and communicates clinical insights to interdisciplinary teams to improve AI-driven diagnostic and treatment tools.

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.

Define and drive the AI and data product roadmap for a regulated B2B SaaS platform. Identify and validate AI-first product opportunities, lead discovery and commercialization, partner with engineering and data science to deliver explainable, auditable AI capabilities, and enable AI across existing products. Engage customers and executives to prioritise use cases, measure outcomes, and establish repeatable launch and governance practices.

Develop, deploy, and operationalize analytical and ML/AI models for cybersecurity use cases. Collaborate with product and engineering teams to enable and migrate production workflows, work with databases and data architectures, create visualizations and reports, adopt new cloud orchestration and data virtualization technologies, and mentor junior cyber data scientists.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

Define and execute Americas logistics and warehousing strategy; lead multi-site DC operations, inbound/outbound logistics, carrier management, trade compliance/imports, P&L oversight, WMS/TMS/ERP optimization, and AI/automation adoption. Requires cross-regional enablement and ~25-40% travel.