Top Machine Learning Jobs in Atlanta, GA

Leads strategy and execution for data products powering threat intelligence solutions. Uses customer insights, big-data analysis, and competitive research to prioritize opportunities, refine API-first products, and integrate data into UI, AI, and third-party workflows. Collaborates with engineering, marketing, sales, and solutions engineering from ideation through launch, influencing stakeholders and executives through data-driven analysis. Requires substantial cybersecurity or data product management experience and expertise in threat intelligence, APIs, analytics, and customer ecosystems.

Leads ExtraHop’s product marketing function, including team leadership, portfolio positioning, messaging, product launches, competitive analysis, sales enablement, content development, integrated campaigns, and executive-level customer and industry engagement. The role requires deep cybersecurity and enterprise technology expertise, strong storytelling and technical communication skills, and collaboration across product, sales, marketing, and partner teams.

Build and lead Precision Neuroscience’s partnership function across the life sciences and healthcare ecosystem. The role owns strategic partnership pipelines, structures and negotiates complex technology and scientific collaboration agreements, advises leadership on deal strategy, translates technical work into commercial narratives, and establishes partnership processes for an early-stage neurotechnology company.

Manages Pulmovant’s enterprise application portfolio, including validated GxP and clinical systems and core IT platforms. Oversees system performance, configuration, compliance, access, documentation, integrations, upgrades, and validation. Partners with Clinical, Regulatory, Quality, Finance, and HR stakeholders, manages vendors and an applications team, and leads continuous improvement, root-cause analysis, and application initiatives. The role also supports AI and machine learning governance, model validation, and responsible data practices.

Build and deploy AI applications, agents, intelligent workflows, document-processing solutions, predictive analytics, and automation. The role spans AI use-case assessment, solution design, prototyping, evaluation, testing, production deployment, monitoring, governance, and responsible-AI controls. The engineer will integrate AI with enterprise systems, APIs, workflows, and data platforms while partnering with engineering, cybersecurity, governance, and mission teams in a federal environment.

Own a broad territory focused on acquiring net-new enterprise customers for SingleStore’s AI and data platform. Build self-sourced pipeline through outbound, account-based, partner, and market-education motions; engage executive and technical stakeholders; develop ROI and TCO cases; navigate complex technical, security, legal, procurement, and negotiation processes; partner with engineers to establish production workloads; and manage forecasting, qualification, CRM hygiene, and new-logo performance.

Lead enterprise AI security architecture, strategy, governance, and secure-by-design implementation across cloud, hybrid infrastructure, software, and AI/ML environments. Design security patterns for LLM hosting, agentic systems, vector databases, and inference endpoints; translate regulatory requirements into technical standards; review complex architectures; implement AI security guardrails and policy enforcement; advise engineering and product teams; and mentor teams while influencing senior stakeholders.

Drives growth by identifying strategic partnerships with enterprise AI and machine learning companies. Develops business development strategies, builds relationships with senior decision-makers, negotiates complex deals, and collaborates with internal teams to implement partnerships. Requires strong AI/ML industry knowledge, executive communication skills, strategic thinking, and adaptability in a fast-paced startup environment.

Leads cross-functional programs that improve products, customer support, and value delivery. Owns execution, coordinates engineering and operations teams, establishes scalable processes, uses data-driven insights to improve customer models, scopes and sequences major initiatives, and communicates progress to stakeholders. The role requires program management experience, strong communication and influence skills, comfort with ambiguity, rapid execution in scaling environments, and interest in AI systems.

Manage customer relationships and AI-focused engagements, serving as a trusted advisor and primary point of contact. Oversee data projects, ensure SLA and delivery goals, coordinate with engineering and operations teams, address client concerns, and translate technical AI and machine learning requirements into actionable project plans.

Manages strategic client accounts for an AI data platform, serving as the primary customer contact and trusted advisor. Oversees data projects, SLAs, quality, and deliverables while coordinating engineering, operations, and project teams. Builds strong client relationships, addresses concerns, translates AI and NLP requirements into actionable plans, and ensures solutions meet customer goals.

Lead finance-focused AI training, evaluation, and data programs across financial analysis, equity research, credit assessment, regulatory compliance, and quantitative modeling. Serve as the finance subject-matter expert, establish quality frameworks, coordinate cross-functional teams, manage timelines, and translate financial expertise for AI/ML teams and financial-services clients.

Conduct hands-on research with frontier AI labs to evaluate model behavior, identify failure modes, and design interventions that improve reliability. Responsibilities include designing evaluations, building data pipelines and fine-tuning workflows, collaborating with internal and external stakeholders, and addressing challenges involving long-context reasoning, tool use, and real-time feedback loops.

Lead customer-centric product development and strategic initiatives for an AI platform. Responsibilities include understanding customer pain points, overseeing product and operations execution, managing accounts, building scalable systems and processes, coordinating with engineering, analyzing performance data, and driving product insights through market and competitive research.

Forward Deployed Engineers embed with customers to identify operational problems, analyze imperfect data, rapidly prototype and deploy AI-powered solutions, and drive adoption. Responsibilities include building pipelines, models, dashboards, optimizers, agents, and operational applications; collaborating with stakeholders; training users; improving platform capabilities; and supporting follow-on customer opportunities. The role requires technical execution, product thinking, client partnership, commercial awareness, and significant travel.

Develop and implement AI-driven applications, workflows, and integrations on the ServiceNow platform. Gather requirements, configure and customize ServiceNow modules, integrate machine learning and NLP capabilities, develop scripts, manage CMDB and service mapping work, test solutions, troubleshoot incidents, and support deployments across environments. The role also involves stakeholder collaboration, documentation, production remediation, and applying ServiceNow AI features such as Now Assist, Virtual Agent, Predictive Intelligence, and Performance Analytics.

Leads data and analytics transformation strategy for major client programs, defining roadmaps, use cases, architecture direction, and operating models. Advises senior stakeholders, facilitates strategy workshops, aligns programs to KPIs and value frameworks, supports governance and risk management, contributes to proposals and pre-sales, and mentors consulting and analytics teams.

Support risk and analytics efforts by performing SQL/Python-based analysis, monitoring portfolio health, building scalable reports, collaborating cross-functionally, and integrating AI tools to surface insights that inform product, risk, and growth decisions.

The Staff ML Engineer will design and operate Samsara's ML platform, collaborating with teams to enhance ML features and improve safety outcomes. Responsibilities include overseeing system reliability, leading technical direction, and mentoring engineers.

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.

Source, develop, and close enterprise health system clients across a US territory. Build relationships with healthcare executives, launch and expand pilot programs, create account plans, meet revenue targets, and transition customers to Client Success. Collaborate with product, legal, marketing, support, and leadership; provide sales forecasts and pipeline reporting in HubSpot; influence the product roadmap; and represent Nabla at industry events.

Designs, builds, and operationalizes production AI agents, LLM systems, RAG pipelines, ML models, and agentic frameworks across major cloud platforms. The role integrates AI solutions with enterprise APIs and workflows, applies MLOps and LLMOps practices, implements observability and evaluation tooling, and embeds with clients to deliver reliable, regulated-enterprise solutions. This hybrid role is based primarily in Dallas with potential consideration for several additional U.S. locations and requires 25%–75% travel.

Develop and launch scalable, user-facing features for AI-powered video and multimedia tools. Architect end-to-end solutions across backend and frontend systems, ensure quality and reliability, collaborate with design, product, and ML teams, and mentor engineers. The role involves rapid prototyping, experimentation, technical leadership, and shaping Pika’s core creative product.

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 Tilt’s product design function across consumer financial products. Set design vision and quality standards, manage and grow a team of six designers and one researcher, build research capabilities, influence product strategy, scale the design system, advocate for users, and partner with Product, Engineering, Marketing, and executive leadership. Drive AI-enabled design practices and ensure product experiences deliver measurable user and business impact.