Top Machine Learning Jobs in Huntsville, AL

The Enterprise Account Executive will manage the complete sales cycle, build relationships with senior leaders, and drive platform adoption within data-intensive organizations.

Design, develop, and implement AI/ML models; analyze large datasets; integrate AI solutions into existing systems; apply MavLink for autonomous systems; collaborate across teams and improve ML development processes.

The Analytics Lead will leverage data analytics to optimize credit strategies, monitor portfolio performance, and collaborate on credit policy with stakeholders across technical and non-technical teams.

Design and build machine learning systems for Coinbase, responsibly use generative AI tools and copilots, apply human-in-the-loop practices, and deliver measurable efficiency, cost, and quality improvements while collaborating in a remote-first environment with periodic in-person surges.

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

The role involves building and optimizing a machine learning and simulation platform, supporting MLOps, model deployment, and infrastructure modernization, while mentoring engineers.

The Digital Engineering Data Solutions Architect will develop data architectures, support system lifecycle management, and collaborate on innovative solutions in national security projects.

Lead architecture, design, implementation, testing, documentation, and deployment of software frameworks and applications. Supervise and mentor engineers, track milestones, conduct reviews, and ensure quality via SDLC and Agile practices.

Manage defense-focused software programs applying AI/ML and weapon-systems engineering. Oversee technical and operational military projects, coordinate stakeholders, ensure program execution under security requirements, and apply Agile, operations research, and integrated air and missile defense expertise.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

Develop large-scale Foundation Models for Autonomous Driving & Robotics, collaborating with teams, optimizing model performance, and mentoring junior members.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

Build and operate ML training and serving infrastructure by designing, developing, and launching backend systems. Collaborate across teams to decompose projects, support operations and on-call, create monitoring and metrics, perform code reviews, and contribute to developer velocity and platform reliability.

Own Cash Application and Deduction Resolution Management products end-to-end. Lead discovery, define requirements, prioritize roadmap, partner with engineering/design/sales, ensure financial accuracy, build ERP integrations, drive launches, and maintain product quality and customer-focused outcomes.

Lead implementation of enterprise AI platforms, governance, and high-impact analytics use cases. Drive end-to-end delivery from experimentation to production, mentor teams, embed responsible AI practices, and partner with cross-functional stakeholders to operationalize AI across the business.

The Enterprise Architect leads architectural strategy and integration for technology and processes while aligning IT investments with business goals. Responsibilities include overseeing cloud modernization, governance, and communication with stakeholders.

The Director of Product Management will oversee the product lifecycle for AI products, focusing on customer collaboration, rapid prototyping, and product strategy. The role involves leading product teams, driving execution, and shaping the product culture.

The VP of Marketing will lead the marketing ecosystem to drive growth, define competitive advantages, influence product design, and mentor a diverse team towards a mission-driven culture.

The SAP Innovation Architect will design SAP automations, mentor engineers, and drive innovation in AI-driven SAP operations, while ensuring scalability and security in integrations.

Lead the development of agentic AI systems for real estate, focusing on long-horizon, supervised experiences. Architect collaborative systems and define success metrics while mentoring a small team.

Lead the design and deployment of RL post-training systems, aligning model behavior with user value and business objectives, while mentoring applied scientists and engineers.

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

The VP will transform R&D operations by embedding AI into product workflows, enhancing efficiency and decision-making across teams. They will lead system redesign, implement AI-driven analytics, and establish KPIs for continuous improvement.