Top Senior Machine Learning Jobs in Atlanta, GA

Lead product strategy, roadmap, and delivery for Falcon Complete’s internal MDR tooling, including AI-powered investigation and triage, ticketing, case management, and analyst workbench systems. Partner with security operations, analysts, engineering, and data science teams to translate workflows into product requirements, prioritize automation, improve analyst productivity and response times, define success metrics, and enhance customer outcomes.

Lead complex insurance technology implementations from discovery through production. Serve as the primary technical contact for integrations between policy administration systems and Akur8’s rating engine, coordinating client IT teams, system integrators, and internal product teams. Support pre-sales discovery, architecture presentations, demonstrations, and statements of work. Conduct workshops, resolve integration issues using payloads and logs, manage risks, create technical documentation and reusable delivery assets, and enable customers to operate the platform independently in English and Spanish.

Leads data ownership and governance for data products, defining metadata, quality, controls, integration, and risk mitigation. Partners with business, analytics, technology, and engineering teams to deliver curated datasets and production-ready solutions. Uses advanced SQL for validation and root-cause analysis, manages workstreams and staff, and supports analytics and machine learning use cases. Applies AI and LLM tooling to automate governance activities and maintains data integrity across regulated environments.

Designs and improves security controls for enterprise AI, ML, generative AI, LLM, agent, and cloud environments. Responsibilities include AI security architecture, threat modeling, application and API security, IAM, data and model protection, monitoring, incident response, automation, and governance. The role partners with cybersecurity, IT, privacy, legal, compliance, data, application, and business teams to secure AI platforms throughout their lifecycle and address risks such as prompt injection, data leakage, excessive agency, and supply-chain compromise.

Drives revenue growth by selling Splunk and Cisco software solutions to large enterprise accounts. Responsibilities include landing, expanding, and deepening opportunities; building executive relationships; developing account plans; managing partners and channels; forecasting pipeline and revenue; coordinating complex deals; and collaborating with sales engineering, customer success, marketing, professional services, and leadership.

Leads enterprise AI strategy, roadmaps, and project portfolios from ideation through deployment. Manages AI scientists and engineers, partners with executives and stakeholders, translates business needs into technical requirements, and drives AI adoption, governance, education, and measurable business impact. Oversees solutions using analytics, machine learning, generative AI, data engineering, and related technologies while establishing success metrics and ensuring timely, budget-conscious delivery.

Leads client-facing generative AI and data modernization engagements, directing solution design, delivery planning, architecture, and technical decisions. Guides teams in prompt engineering, context engineering, agent orchestration, LLM evaluation, RAG, vector databases, and AI guardrails. Oversees cloud AI implementations using Gemini, Vertex AI, AWS Bedrock, or Azure AI Services; develops Python prototypes; evaluates model performance; manages workstreams and deliverables; and mentors staff on AI methods, agile delivery, and technical problem-solving.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

Leads Google Cloud AI and machine learning engineering teams and client workstreams. Oversees generative AI, LLM application, agent orchestration, retrieval-augmented generation, model evaluation, prompt engineering, guardrails, and LLMOps initiatives. Reviews architecture, code quality, testing, and solution delivery using Vertex AI, LangChain, LangGraph, Python, and LLM APIs. Coaches team members, improves reusable delivery assets, and manages client relationships, timelines, quality, and expectations.

Leads client-focused generative AI and data modernization architecture, translating business needs into scalable solutions using Google Cloud, Vertex AI, LLMs, vector databases, and modern data platforms. Advises stakeholders, develops AI evaluation and guardrail practices, guides experimentation and deployment, presents technical recommendations, supports proposals, and coaches teams through complex transformation programs.

Leads category and innovation analytics intelligence for global business planning and performance routines. Delivers insights for business reviews, identifies growth opportunities, improves analytics tools and workflows, drives adoption, ensures data integrity, and influences senior stakeholders across marketing, commercial, finance, strategy, and technology. Requires strong data storytelling, category analytics, advanced analytics, collaboration, and stakeholder management experience in FMCG environments.

Leads enterprise AI cybersecurity strategy, including AI-enabled threat detection, automated response, AI security controls, adversarial testing, and emerging technology risk management. Advises executives and cross-functional teams on securing LLMs, ML pipelines, agentic systems, and AI products. Builds and manages an AI security and automation team, establishes technical standards and metrics, oversees vendors, and guides risks involving prompt injection, data poisoning, model leakage, quantum computing, and post-quantum cryptography.

Leads complex technology risk remediation engagements across enterprise organizations. Coordinates stakeholders, tracks commitments and decisions, validates remediation plans and control effectiveness, assesses residual risk, prepares executive reporting, and escalates blockers. The role ensures remediation is structured, evidence-based, accountable, and focused on measurable risk reduction without owning implementation.

Leads revenue operations across Sales, Partner, and Customer Success, owning pipeline management, forecasting, territory planning, KPIs, dashboards, systems, and process improvement. Partners with Finance, Analytics, Product, and leadership to translate go-to-market strategy into scalable execution. Manages AI-enabled sales tools, reporting, automation, operating cadences, and a high-performing operations team while driving revenue growth, retention, expansion, and customer outcomes.

Build scalable systems and machine learning models that transform satellite imagery into labeled geospatial data and production computer vision products. Responsibilities include developing data and annotation pipelines, tracking lineage and versioning, deploying inference services, evaluating models, supporting cloud infrastructure, and improving labeling workflows. The role requires strong Python, cloud, containerization, CI/CD, infrastructure-as-code, production support, and deep learning expertise, with preferred experience in GCP, Vertex AI, spatial databases, and satellite imagery.

Leads the development and global scaling of Fuelight, an AI-enabled resource allocation and investment optimization product. Responsibilities include building production machine learning applications, MLOps capabilities, scalable architectures, decision-support experiences, explainable AI features, and integrations with data and optimization products. Partners with engineering, data science, product, and business stakeholders while establishing engineering standards and ensuring cybersecurity, privacy, responsible AI, and governance compliance.

Leads end-to-end solution architecture for complex healthcare payer initiatives spanning claims, billing, enrollment, provider management, cloud modernization, and AI capabilities. Defines reusable architecture patterns, governs design decisions, translates designs into implementation artifacts, and mentors architects and engineering teams. The role partners with product, development, IT, and leadership teams to deliver cloud-native, event-driven, API-first, and AI-enabled solutions across enterprise platforms.

Conducts quantitative analytics, credit risk model development, validation, stress testing, and model risk management. Responsibilities include developing loss forecasting and scorecard models, analyzing large financial datasets, documenting methodologies, monitoring model performance, addressing validation findings, and communicating results to risk management, senior leaders, and regulators. The role also requires collaborating across technology and business teams, improving analytical processes, and supporting regulatory capital modeling in a controlled, audited environment.

Lead revenue generation for Squark AI by building enterprise pipeline, selling AI software and related agency services, closing complex B2B deals, and shaping repeatable go-to-market strategy. The role owns prospecting through close, executive relationship development, ROI-based business cases, pricing, negotiations, forecasting, CRM discipline, and cross-functional collaboration with product, marketing, analytics, and delivery teams.

Drive product and business impact through statistical modeling, experiment design, Bayesian marketing analysis, machine learning, NLP, LLM applications, and classifier implementation. Build growth metrics, monitoring pipelines, evaluation datasets, and AI trigger systems across search and Duck.ai. Analyze privacy-constrained data, deploy production-grade models, optimize SQL queries, and lead complex projects from scoping through production with minimal direction.

Own strategy and roadmap for Crunchbase's customer-facing AI data layer. Identify and validate model-derived data products, lead cross-functional development, set quality standards, drive adoption and monetization, and monitor performance and product economics.

Lead enterprise payments architecture for card-present solutions, provide technical governance and guidance, integrate AI-enabled capabilities securely, develop and review production code, evaluate emerging technologies, and drive architecture decisions across product families.

Own the strategy, roadmap, requirements, launch, adoption, and success metrics for a technical platform. Partner with engineering, data, product, and business teams; evaluate architecture, APIs, and system tradeoffs; prioritize foundational investments against customer and revenue outcomes; and apply AI to improve platform capabilities. The role requires strong product management experience, technical depth, analytical skills, and production experience with LLM-based or ML-adjacent products.

Provides strategic legal counsel on global privacy, data governance, cybersecurity, and AI regulations. Leads enterprise data governance frameworks, classification, retention, access, sharing, deidentification, and responsible data-use initiatives. Drafts data processing, data sharing, AI, privacy, and security agreements; partners with product, engineering, security, compliance, and government affairs teams; develops policies and training; and leads regulatory inquiries, audits, investigations, and litigation readiness.

Lead analytics for billing and payments across digital and assisted channels. Develop measurement frameworks, KPIs, dashboards, and automated reporting; conduct advanced analyses, root-cause investigations, forecasting, anomaly detection, and data validation. Apply AI-enabled tools to improve insight generation and decision support, ensure data quality, and communicate recommendations to executives. Partner with cross-functional teams, lead strategic analytical initiatives, promote self-service analytics, and mentor analysts.