Top Remote Machine Learning Jobs in Atlanta, GA

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

As a Staff Applied ML Scientist, you will develop and maintain fraud detection models, conduct research on fraud types, and collaborate across teams to drive product development and real-time decision-making.

As a Senior Applied ML Scientist, you'll develop fraud detection models, research new fraud types, and write production code while collaborating across teams to enhance SentiLink's identity verification solutions.

Design, train, and productionize machine learning models for fraud and identity risk across the full ML lifecycle. Research new fraud types, perform feature engineering and labeling, write production-ready code for real-time decisioning, monitor models, and provide analyses to inform product, sales, and data acquisition.

Own end-to-end analytical lifecycle to develop and optimize business, risk, and growth strategies. Monitor portfolio and macro trends, build and interpret ML-driven models, lead cross-functional launches, mentor junior analysts, and build AI-assisted workflows to improve decisioning and measurement across products and geographies.

Lead global 24/7 security operations and the full incident response lifecycle. Direct cyber threat intelligence and convert it into detection coverage and defensive architecture. Establish detection-as-code and continuous validation practices, coordinate cross-functional incident response, integrate automation/ML, and build a diverse, distributed team focused on adversary-focused detection and rapid, measured defensive actions.

Advise state agencies on AI strategy and roadmaps, prioritize use cases, assess readiness and data maturity, define responsible AI governance, facilitate stakeholder workshops, and support early-stage implementation and adoption planning.

Independently validate and monitor machine learning models for credit underwriting, credit risk, and fraud detection. Identify model weaknesses, recommend improvements, and collaborate with model owners to remediate findings. Support and maintain the Model Risk Management framework and coordinate with Internal Audit, Internal Controls, and Compliance on audit and regulatory requests.

As a Machine Learning Engineer II, you will enhance AI systems for automating customer operations, develop evidence extraction pipelines, and collaborate with teams on model development and deployment.

Own and set technical direction for the Everand backend, building scalable, reliable systems for discoverability, personalization, and core consumption journeys. Drive architecture, platform health (CI/CD, staging, DBs, queues, cost, observability), mentor engineers, lead cross-team planning, modernize legacy systems, and partner with product, design, analytics, web/mobile, and ML to support experimentation and telemetry-driven decisions.

Own end-to-end compliance issue management for Lemonade's personal lines insurance products: identify, track, prioritize, remediate, and report issues; analyze data for root causes and trends; build remediation plans; recommend risk-based priorities to leadership; engage regulators; and develop AI/automation tools and cross-functional reporting to improve compliance processes.

Lead integrated paid media strategy and execution across channels, modernize media planning with technology and data, manage agency/vendor relationships and multimillion-dollar budgets, build media capabilities and teams, and deliver executive insights to optimize ROI using AI, automation, and advanced measurement.

Serve as primary post-sales strategic partner for largest enterprise clients, driving AI Agent adoption, ROI, optimization, governance, renewals, and cross-functional advocacy to turn customers into champions.

Senior pre-sales engineer who partners with sales and channel teams to present Snowflake, run demos and proofs-of-concept, design solutions, and close large enterprise deals. Requires deep expertise in databases, cloud data architectures, ML/generative AI, SQL and Python, and the ability to engage both technical and executive stakeholders.

Own growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. Productize ML capabilities into creator-facing workflows, partner with research and engineering, run experiments and analytics (e.g., Amplitude), conduct customer research, and leverage AI tools to accelerate shipping and internal insight systems.

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

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Design, build, and ship production AI agents integrated end-to-end into a TypeScript/Node.js/React stack. Apply ML judgment to product decisions, improve agent reliability and evaluations, and move quickly in a startup environment owning ambiguous problems.

Transfyr seeks adaptable builders for various roles across CS, biology, and business. Responsibilities include developing sensor stacks, data harmonization, computer vision, machine learning systems, lab operations, project management, and business development.

Drive U.S. strategic growth by identifying, developing, and closing complex enterprise deals in the Databricks ecosystem. Build executive relationships, lead co-sell motions with partners, design account plans, and partner with Sales, Engineering, and Delivery to ensure successful execution and long-term value. Own CRM updates and relay market feedback to shape offerings and GTM strategy.

Lead strategy and execution to prevent, detect, and disrupt digital fraud, scams, and money mule activity. Build and mentor data science and analytics teams, develop ML predictive models, partner with product, cyber, vendors, and risk teams, and drive prevention-first controls, compliance, and operational efficiencies across payments, onboarding, and authentication channels.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Design and implement scalable backend and distributed systems for a marketing intelligence platform. Build near-real-time ingestion and processing, scale an incrementality/experimentation product, integrate AI-powered workflows, improve data ingestion/exports and connection-state systems, and contribute frontend components to deliver end-to-end product experiences.

Lead a Big Data Engineering team to deliver production-grade ETL and data pipelines at scale. Own team execution, code quality, morale, and roadmap execution with product managers. Remove roadblocks, coach and develop engineers, promote engineering best practices, and enable data-driven and AI-powered product features (personalization, recommendations, search, ranking, matching).

Evaluate and strengthen AI model behavior on cybersecurity topics by writing expert prompts, annotating and grading model responses for accuracy and safety, and applying structured guidelines to classify sensitive content. Work part-time on AI safety tasks with emphasis on secure, responsible handling of dual-use information.