Top Machine Learning Jobs in Atlanta, GA

Leads Oracle Cloud ERP and EPM finance transformation implementations, setting strategic direction, managing complex projects, developing client relationships, improving finance processes, and mentoring emerging leaders. The role requires extensive Oracle Cloud implementation experience, strong business process expertise, market development, client networking, presentation skills, and team leadership.

Leads a regional Solutions Consulting team supporting customer acquisition, product adoption, revenue growth, and customer value. Responsibilities include coaching consultants, supporting presales activities such as proof-of-value presentations and RFPs, developing sales and delivery strategies, resolving escalations, providing observability thought leadership, and partnering with account executives and technical customer teams. The role requires deep SaaS and technical expertise, leadership experience, and strong customer-facing communication skills.

Staff Software Engineer responsible for designing and implementing resilient, scalable, high-performance healthcare software across the full application stack. The role develops frontend and backend services using VueJS, NodeJS, Java, Spring, AWS, databases, and APIs; contributes to technical and product strategy; promotes testing and engineering excellence; and works independently across distributed systems. Preferred experience includes generative AI, machine learning, Kafka, data pipelines, statistics, and healthcare technology.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads Fenergo product consulting engagements focused on AML, sanctions, data analytics, and regulatory risk solutions. Manages client accounts, oversees project planning and execution, guides analytics initiatives, and develops data-driven business strategies. Uses predictive analytics, machine learning, statistical modeling, and scenario analysis to generate insights. Manages and mentors teams, engages stakeholders, resolves conflicts, promotes innovation, and ensures high-quality deliverables and adherence to professional standards.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Leads multidisciplinary teams developing, modeling, testing, integrating, and demonstrating signal processing, optimization, machine learning, radar, and electronic warfare algorithms. Responsibilities include developing RF and sensing system concepts, directing simulations, supporting laboratory and field test evaluations, assessing performance, translating customer requirements into research priorities, and presenting technical findings to customers and senior stakeholders.

Deploy AI solutions into production environments, assess business processes, define success metrics, and partner with engineering, data science, and platform teams. Monitor adoption, performance, and operational risk while using stakeholder feedback to prioritize improvements. Contribute to deployment standards, governance frameworks, documentation, operational readiness practices, playbooks, and repeatable methodologies for responsible AI adoption.

Leads technology, data, automation, analytics, and applied AI solutions supporting investment manager research across public and private markets. Translates business requirements into scalable production systems, develops applications and dashboards, improves data quality and governance, and prototypes AI/LLM capabilities. Partners with research, investment, data, technology, operations, and vendor stakeholders while managing complex initiatives, controls, priorities, and adoption.

Develop and support software, automation tools, dashboards, and alarms for cloud infrastructure, cost attribution, and cloud efficiency. Collaborate with cross-functional teams and senior engineers to design reliable systems, APIs, databases, tests, and AI agents. Contribute to architecture and automation strategies while maintaining strong security, communication, and delivery practices.

Manage a portfolio of advertisers on the Adflow commerce media platform, building relationships, monitoring budgets and campaign performance, presenting business reviews, coordinating onboarding, recommending optimization strategies, and identifying revenue-growth opportunities. The role serves as the primary client contact, collaborates with internal campaign, media operations, creative, and finance teams, and uses performance marketing expertise and analytics to drive advertiser success and long-term partnerships.

Manage a portfolio of advertisers on the Adflow commerce media platform. Responsibilities include client onboarding, campaign coordination, budget and revenue pacing, performance reporting, business reviews, strategic recommendations, optimization feedback, and identifying opportunities to grow advertising spend and channel distribution. The role serves as the primary client contact while collaborating with business development, campaign strategy, creative, media operations, and finance teams.

Lead agile design and development projects for mobile apps and digital products. Coordinate product, design, engineering, marketing, leadership, and client stakeholders; manage project plans, scope, requirements, backlogs, acceptance criteria, deadlines, workflows, and deliverables. Support scoping and client relationship management while ensuring successful end-to-end software launches and alignment with business objectives.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.

Analyzes workforce and healthcare data to identify trends, build predictive and machine learning models, and deliver actionable recommendations. Uses Python, Alteryx, and Power BI for analytics, visualization, and reporting. The role supports workforce strategy, employee engagement, organizational effectiveness, talent management, and healthcare cost insights. Responsibilities also include client collaboration, relationship management, team guidance, and applying risk adjustment and medical economics concepts to inform strategic decisions.

Leads teams designing and deploying AI-driven enterprise and cloud security solutions. Responsibilities include developing machine learning systems, integrating data infrastructure and pipelines, performing advanced modeling and analysis, and building AI applications with Python, Java, and C++. The role involves client engagement, strategic problem-solving, stakeholder validation, coaching, process innovation, and operational excellence while addressing complex cybersecurity and privacy challenges.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Leads internal audit and SOX engagements, manages client relationships, develops audit methodologies, evaluates financial statements and internal controls, conducts risk assessments, and oversees audit reporting. The role includes project ownership, budgeting, stakeholder management, team leadership, mentoring, process improvement, and use of AI and risk technology to enhance audit effectiveness and address compliance and governance risks.

Supports intelligent automation projects across requirements gathering, RPA workflow development, process mining, data analysis, dashboard creation, testing, deployment, and documentation. The intern will explore prompt engineering, LLM-powered features, AI agents, guardrails, and machine learning automation. Responsibilities also include reviewing model outputs, identifying process improvements, coordinating project updates, and collaborating with analytics and automation teams under mentorship.

Support solutions and enterprise architecture activities by creating architecture documents and Visio diagrams, researching cloud, DevOps, generative AI, and machine learning trends, maintaining architecture repositories, and participating in technology project delivery. The intern will gain exposure to AWS, Azure, Google Cloud, CI/CD, GitHub, platform engineering, integration, analytics, and cross-functional collaboration while contributing innovative solutions.

Develop and operate production ML and AI systems powering patient experiences such as matching, ranking, recommendations, onboarding, and personalization. Build reusable ML infrastructure, pipelines, evaluation, observability, and model-serving capabilities. Provide technical leadership across the ML lifecycle, guide architecture, evaluate custom versus foundation-model approaches, and partner with ML and Patient Engineering teams to deliver reliable, scalable AI products.

Leads the AI Engineering team across applied AI features and foundational ML infrastructure. Responsibilities include managing Senior and Staff engineers, hiring and coaching, deploying LLM-powered capabilities, building MLOps and AI observability platforms, balancing product delivery with platform investment, and ensuring privacy, compliance, evaluation rigor, and clinical safety in production systems.

Own the strategic vision and roadmap for Coursera’s AI-driven search experience. Lead conversational search, personalization, semantic and multilingual search, ranking, and discovery improvements. Partner with engineering, design, research, data science, ML, marketing, and partnerships teams to deliver scalable platform capabilities. Use experimentation, market analysis, KPIs, and customer insights to improve conversion, merchandising, learner experience, and revenue.

Set the technical vision for data science, lead complex statistical and machine learning model development from concept through production, and architect scalable modeling platforms and pipelines. Develop credit risk, pricing, and loss forecasting models; establish model governance standards; partner with senior leaders; mentor data scientists; and communicate technical strategy to executives. The role emphasizes production deployment, monitoring, cloud architecture, and high-impact decision-making across the business.

Designs and delivers technical solutions, including AI models and workflow automations, for Business Operations and Client Services. Responsibilities include gathering requirements, developing and validating machine learning solutions, improving Aladdin platform capabilities, managing stakeholder relationships, identifying process risks, and measuring business benefits. The role requires programming, SQL, machine learning, NLP, cloud platform, RPA, visualization, and Agile experience.