Top Machine Learning Jobs in Atlanta, GA

Lead development of analytical pipelines and algorithms for multimodal wearable and biomechanics data. Collect, process, and analyze gait, locomotion, and physiological datasets; apply signal processing, sensor fusion, statistical modeling, and ML. Validate wearable systems against laboratory gold-standards, produce technical reports and visualizations, and collaborate with multidisciplinary teams on client-facing consulting work.

Lead and manage an AI engineering team to design, develop, and integrate machine learning and deep learning solutions across business units, provide technical leadership and best practices, collaborate with cross-functional teams, and stay current with AI advancements to drive continuous improvement.

Lead revenue generation for Squark AI by building pipeline, running consultative enterprise sales, and closing complex software-plus-services deals for nonprofit fundraising. Shape commercial strategy, package bundled services, translate AI use cases into ROI, manage forecasting and CRM hygiene, and collaborate cross-functionally to create a repeatable go-to-market motion.

Design, deliver, and maintain revenue-optimizing analytics and optimization products. Identify commercial opportunities, build models (forecasting, RL, optimization), process large/unstructured data, coordinate stakeholders and IT, implement end-to-end solutions, and support Analytics team development.

The Senior Product Manager will oversee product development in the LATAM market, focusing on infrastructure, product strategy, and user engagement metrics while coordinating with various stakeholders.

Lead architecture, design, implementation, and global rollout of Varicent ICM solutions. Translate compensation plans into scalable Varicent Designer/Studio configurations, integrate with Salesforce/SAP/Workday, enable AI/ML use cases, enforce governance/SOX controls, manage upgrades, mentor teams, and support stakeholders across Sales, Finance, and IT.

As an Enterprise Account Executive at Salesforce, you will drive revenue growth by leveraging AI-driven solutions, understanding client needs, and demonstrating how Agentforce can solve business challenges while fostering client relationships.

Design and maintain enterprise data architecture and pipelines to integrate legal and business systems. Define data strategy, governance, and analytics infrastructure. Support practice groups with legal technology, AI/ML integration, vendor assessments, documentation, training, and risk/compliance controls across marketing, finance, HR, and legal operations.

Work with sales and partners to solve complex customer problems, deliver value-based demos and proofs of concept, map customer architectures to Snowflake Data Architecture, support design and implementation, and help close large enterprise deals while maintaining expertise in data warehousing, ETL, analytics, and ML/generative AI.

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.

Lead middle-office trade lifecycle from capture through settlement across equities, fixed income and complex assets. Manage trade matching, confirmations, corporate actions, reconciliations, controls and stakeholder relationships. Drive process improvement and automation (AI/RPA), ensure regulatory/compliance adherence, deliver reporting, and coach onshore and offshore teams to optimize settlement efficiency and reduce exceptions.

The Client Partner will drive adoption of the Aera Decision Cloud by engaging with senior executives at enterprise clients, identifying opportunities, and managing client relationships. Responsibilities include strategic planning and achieving revenue targets in a consultative sales approach.

The Sr. Manager of Information Risk & Controls drives the risk management evolution by leading risk identification, developing frameworks, and collaborating with teams across Invesco.

As Director, Global Deal Desk, you'll architect the Quote-to-Cash process, integrate AI automation, mentor teams, and optimize deal negotiations for revenue capture.

The Senior Director, Data Scientist will lead data science projects, manage data pipelines, implement data strategies, and mentor teams while influencing business strategy with data insights.

Lead development of digital twin and simulation models for warehouse operations, deploy AI-driven decision systems, build forecasting and optimization models, validate experiments linking operational metrics to financial impact, and partner with engineers, operations, and external AI/academic partners to scale innovations across fulfillment networks.

The Data Scientist will optimize global shipping using data science to build predictive models, create dashboards, and enhance operational performance. Requires strong skills in AI and collaboration.

Lead the Logistics Insights team to convert data into actionable insights using advanced analytics, AI/ML, and automation. Own the logistics analytics roadmap, partner with leadership to deploy digital capabilities, improve service, cost, and capacity agility, and establish data governance and enterprise-ready reporting to drive measurable operational improvements.

Design, build, and deploy production-grade ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM applications, and scalable data pipelines with observability and MLOps practices for cloud and on-prem environments.

Design, build, and deploy production ML systems for ICS/xOT cybersecurity, including threat detection, anomaly detection, NLP/LLM features, data pipelines, observability, MLOps, and containerized deployments across cloud and on-prem environments.

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

The Head of Education & Community at Siena is responsible for developing product education, onboarding programs, community events, and market education resources. This role involves creating curricula, conducting workshops, and supporting sales with training and demos while leveraging AI for teaching efficiency.

Build and scale predictive models and ML-driven forecasting for FP&A; develop data pipelines, model governance, monitoring, and self-service analytics; generate actionable financial insights and drive AI adoption across finance while ensuring data integrity and communicating results to leadership.