Top Senior Machine Learning Jobs in Atlanta, GA

Leads a data science team focused on customer intelligence and personalization across digital products, apps, newsletters, and marketing channels. Develops lifetime value, segmentation, retention, recommendation, attribution, forecasting, and engagement models. Owns product funnel analytics and experimentation, including A/B testing and causal inference. Partners with Product, Marketing, Editorial, Data Operations, and Engineering to translate customer behavior into product improvements, measurable growth, and scalable data capabilities.

Analyze and characterize conversational audio data, identify underrepresented areas, and build active-learning and human-in-the-loop workflows. Develop representative benchmarks, automate model adaptation, and create reusable data analysis and scoring systems. Partner with research, engineering, and data teams to run experiments, improve models, organize data, and translate complex findings into measurable product improvements.

Lead the In-Vehicle Experience team at Samsara, focusing on transforming in-cab cameras into intelligent companions. Collaborate with engineering, prioritize features, and ensure client interactions highlight trust and connection. Conduct customer research and integrate AI and ML into product features.

Lead independent validation and ongoing monitoring of complex financial and analytics models, including ALM, loss forecasting, loan transition, corporate finance, and engagement models. Identify weaknesses, communicate findings, guide remediation, and strengthen model governance. Collaborate with Finance, Quantitative Research, Growth Analytics, Internal Audit, Internal Controls, Accounting, and Compliance to maintain Affirm’s model risk framework and address audit, regulatory, and examiner requests.

Lead deployment, configuration, optimization, and operational support of CrowdStrike Falcon AI/ML detection and response capabilities. Tune ML models, build automation playbooks, develop scripts using Falcon APIs, integrate AI features with customer toolchains, support incident response and threat hunting, deliver customer workshops, and mentor team members. Travel up to 25%.

Partner with healthcare clients to design, prototype, and deploy production-grade AI/LLM solutions. Lead discovery, architecture, cloud integration, and delivery while troubleshooting distributed systems and driving measurable client outcomes.

Own Secret Detection and Vulnerability Research as a product: define strategy across prevention, detection, validation, revocation, and reporting; ship detection content and intelligence with measurable quality; drive adoption, retention, and revenue; partner with engineering, research, and Field; use AI to accelerate research and productization.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

Lead design, build, and deploy scalable, reliable Java-based microservices in a cloud-native, event-driven AWS environment. Own backend feature design, code quality, automated testing, and FedRAMP release processes. Mentor engineers, participate in on-call/TechOps, integrate AI tools into development, and drive architecture, observability, and cross-team initiatives.

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

Lead and manage the underwriting and credit risk model validation team, perform hands-on independent validations of complex ML models, assess data integrity and performance, identify and remediate model weaknesses, partner on MRM framework improvements, and coordinate with audit, compliance, and controls to meet regulatory standards.

Lead the development of machine learning systems for Cedar Pay's Personalization Engine, manage ML engineers, and ensure ML model effectiveness.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

Lead and transform the Fraud Intelligence Team by designing scalable operating models, QA and measurement frameworks, and talent programs. Drive labeling quality, operational metrics, and fraud prevention impact; convert frontline fraud observations into insights for Product, R&D, Analytics, and GTM; leverage AI, automation, and tooling; and serve as a cross-functional fraud subject-matter expert while developing early-career talent and measurable business outcomes.

Designs and implements Dynamics 365 Finance solutions supporting General Ledger, payables, receivables, cash management, fixed assets, consolidations, integrations, reporting, and financial processes. Leads fit-gap analysis, project delivery, optimization, AI and automation initiatives, stakeholder engagement, audit support, training, mentorship, and finance systems activities related to mergers and acquisitions. Advises leadership on D365, Power Platform, Copilot, data, and emerging Microsoft technologies.

The Data Security Architect will design secure architectures for data protection in cloud and hybrid environments, partnering with various teams to embed security in systems and mentoring engineers.

Build and enhance an ML platform supporting the full model lifecycle, scalable training and real-time prediction services, expand NLP capabilities, design data engineering solutions, maintain production reliability, and mentor junior engineers.

Leads data management and technical delivery for life sciences consulting engagements. Develops predictive models and advanced analytics using large healthcare datasets, including claims, EHR, payer, sales, formulary, and coverage data. Builds internal tools, automates workflows, documents processes, presents insights to stakeholders, and coaches data engineers and junior staff. Supports pharma and biotech clients with product planning, pricing, reimbursement, commercialization, and regulatory solutions.

Lead software engineering teams in designing, developing, testing, and delivering enterprise applications. Responsibilities include consulting with Fortune 500 clients, managing projects, gathering requirements, architecting solutions, coding, presenting findings, mentoring junior developers, and using cloud, AI, machine learning, IoT, and modern software technologies. The role follows an agile, collaborative approach and operates in a hybrid model.

Leads technical consulting engagements, overseeing teams, client relationships, solution architecture, and delivery across software engineering, cloud, data, AI, machine learning, and DevOps. Manages project planning, estimation, Agile SDLC execution, risks, resources, and stakeholder communication. Develops high-performing teams through coaching and mentoring, supports recruiting and business growth, and applies responsible AI-assisted engineering practices.

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

Supports FP&A and enterprise analytics by developing scalable Power BI reporting, financial models, dashboards, and automated processes. Analyzes financial and operational datasets to identify trends, risks, and opportunities; improves forecasting, budgeting, and recurring reporting workflows using Excel, Python, SQL, Power Automate, and Microsoft platforms. Collaborates with finance, data engineering, IT, and business stakeholders, trains users, maintains governance standards, and contributes to the Pigment planning platform. Evaluates AI-enabled tools to improve reporting efficiency, data quality, and decision-making.

Leads enterprise assortment strategy and AI-enabled planning transformation across channels, categories, markets, and customer segments. Oversees assortment optimization, predictive modeling, machine learning, inventory placement, SKU rationalization, financial performance, governance, and intelligent decision-support systems. Partners with merchandising, supply chain, finance, technology, and data science leaders while directing a multidisciplinary organization of planners, analysts, data scientists, engineers, and BI specialists. Drives executive alignment, organizational change, AI adoption, talent development, and measurable improvements in sales, margin, inventory productivity, and customer satisfaction.

Leads procurement governance, operating standards, project portfolio oversight, AI adoption, digital transformation, continuous improvement, executive reporting, financial analysis, compliance, and supplier performance initiatives. Establishes frameworks, KPIs, dashboards, workflows, and knowledge systems while coordinating procurement with facilities management and other operational stakeholders.

Advise clients on antitrust eDiscovery compliance using machine learning and generative AI. Build and validate TAR/AI models (Epiq AI, Relativity, Reveal, Brainspace), craft LLM prompts, draft defensible protocols, train/transfer workflows to review teams, and support client-facing, pre-sales, and thought-leadership activities. Must manage multiple projects and meet deadline-driven schedules.