Top Remote Machine Learning Jobs in Atlanta, GA

The role involves leading strategic AI partnerships, driving revenue growth, and managing cross-functional teams while advocating for AI initiatives internally and externally.

Lead strategy and execution for fraud risk management across the platform. Develop detection and prevention frameworks, optimize transaction screening, partner with Compliance, Data Science, Engineering and Product, oversee KPIs and vendor costs, lead a risk strategy team, and pilot AI/LLM-driven tools to enhance detection while enabling business growth and regulatory alignment.

Design, build, and maintain scalable AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists and engineers to implement and optimize AI solutions, troubleshoot pipeline issues, document best practices, and develop MVP code to transition into production-ready systems.

Lead global sales enablement strategy and programs to drive revenue, product adoption, and GTM readiness. Oversee product-aligned enablement teams, launch readiness, content and demo strategy, CRM and tool adoption, measurement frameworks linking enablement to outcomes, and integration of AI into enablement.

The VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven culture.

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.

Lead Billtrust's Applied Intelligence product strategy, build and scale AI product teams, define governance and evaluation standards, translate frontier AI into production-grade AR solutions, and represent the company externally to drive commercial impact and customer co-creation.

As a Senior Staff Machine Learning Engineer, you will drive AI product development, collaborate with cross-functional teams, and enhance ML models at scale.

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.

Senior individual-contributor product manager owning agentic and platform capabilities: define API/MCP/headless surfaces, non-functional requirements (scale, performance, reliability, security), and agentic workflows. Set product strategy and roadmap, write specs for engineering, partner with AI/ML, Data Science, Professional Services, and customer teams, and ensure auditability and regulatory readiness for enterprise financial customers.

Act as the technical lead in enterprise sales: run technical discovery, design and deliver customized demos and POCs, assess API/cloud/model fit, address technical objections, support contract negotiations, and relay product feedback to engineering while staying current on AI/ML trends.

Lead technical strategy and architecture for Azure Storage geo-replication, data protection, failover orchestration, and business continuity. Drive cross-team delivery, operational excellence, telemetry, automation, AI-assisted operations, and represent the team in executive and customer engagements.

Lead a centralized Data Science & Engineering team to build scalable data pipelines, productionize ML/AI solutions, ensure data governance and reliability, partner with cross-functional stakeholders to prioritize initiatives, and drive platform improvements for analytics, personalization, and product features.

Lead healthcare and pharmaceutical marketing analytics: analyze CRM, media, healthcare and behavioral data; build segmentation, attribution, audience scoring, and predictive models; develop measurement frameworks; use Python, SQL, BI and automation; translate insights for executives; mentor juniors and partner with Strategy, Media, and Client Services.

Lead design, build, and operation of data architecture, pipelines, and semantic layers. Manage sprint planning, DevOps metrics, data quality and monitoring, and MLOps enablement. Partner with stakeholders, coach engineers, track project plans, and ensure data availability, accuracy, and documentation.

Manage and grow strategic partnerships across US & Canada for a Google Cloud-focused AI and data consultancy. Drive co-sell initiatives, GTM planning, partner enablement, joint marketing, event execution, partner onboarding, and pipeline generation while tracking partner performance and reporting impact.

Lead strategy and build 0->1 AI products that streamline complex healthcare workflows across providers, pharmacies, patients, and pharma partners. Own roadmap, requirements, metrics, and product performance; partner with engineering, data, clinical, and commercial teams to launch and iterate AI-enabled solutions that drive adoption and measurable business and patient outcomes.

Lead enterprise business systems (NetSuite, Salesforce, Workday, Boomi) strategy and delivery. Architect integrations and AI/ML workflows, manage delivery teams and vendors, improve SDLC, ensure data alignment with analytics, and drive automation to increase operational efficiency and measurable ROI.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

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.

Define and execute the companys AI strategy; build and lead the data science, ML engineering, and AI teams; govern intake, prioritization, and AI guardrails; advance production ML, MLOps, LLMs and agentic workflows; partner cross-functionally to deliver measurable ROI; and report AI impact and roadmap to the CEO and board.

Lead and rebuild Fuel Cycle’s enterprise sales engine: define GTM strategy, generate new-logo pipeline, coach a growing sales team in insight-led selling, drive enterprise deal execution with C-suite stakeholders, deliver accurate forecasting, and partner cross-functionally to maximize revenue and retention. Responsible for quota attainment, board reporting, and establishing scalable sales processes.

Lead backend architecture and implementation for scalable, reliable cloud-hosted web products. Mentor engineers, set standards, integrate agentic AI coding tools, design systems applying ML to large datasets, and balance customer-facing features with technical debt and performance.

Lead end-to-end product areas that improve build speed, cost accuracy, margin, and throughput. Own strategy, roadmap, and execution for complex financial and operational data products, integrate AI/ML into workflows, write precise requirements, instrument metrics, run experiments, and drive cross-functional outcomes with construction, finance, sales, design, and engineering teams.