Top Senior Machine Learning Jobs in Huntsville, AL

Design, build, and scale backend systems and APIs for high-transaction consumer products. Collaborate with product, credit, compliance, support, and analytics teams. Contribute to code reviews, technical planning, security, and operational excellence. Mentor peers and promote engineering best practices.

Design, implement, and scale ML-based solutions for search and advertising; define data collection, evaluation, and production serving strategies; analyze data to inform development; communicate cross-functionally; produce technical reports; and stay current with advances in LLMs, vision models, and generative AI.

Industry Expert who reviews and defends advanced AI/ML and systems engineering projects, chairs architecture and executive review panels, hosts occasional technical sessions, and sets standards for instructors. The role requires production-scale engineering experience, live architecture critique, a public technical footprint, strong English, and expertise in agentic systems, LLM evaluation, model serving, cloud infrastructure, distributed systems, observability, RAG, and enterprise deployments.

Lead the integration of AI and digital solutions in manufacturing processes, driving adoption and measurable impact on efficiency, quality, and performance.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

Design, build, and deploy machine learning systems for controlling quantum processors. Develop reinforcement learning and Bayesian methods for QEC calibration, and work cross-functionally with product and R&D teams.

The Senior Technical Architect will lead AI SDLC transformations, create architectural solutions, mentor teams, and drive innovation in regulated industries.

Own the full lifecycle of clinical text extraction models, from problem framing and annotation strategy through production deployment, evaluation, monitoring, and retraining. Build clinical NLP pipelines, establish defensible quality and error-analysis systems, and apply LLMs using rigorous evaluation, observability, and cost controls. Partner with clinical data and backend engineering teams while addressing PHI protection, de-identification, auditability, and access controls. As the first ML hire, set technical direction and potentially build and lead the future ML team.

Lead end-to-end product strategy and delivery for a core marketplace area, collaborating with engineering, UX, and design. Conduct qualitative and quantitative research, run agile sprints, measure results with analytics, and pioneer AI/ML product features and workflows to improve user experience and platform impact.

Lead document-vision research and production systems for multimodal legal evidence understanding. Define evaluation standards, frame hard problems, design and ship models, run efficacy studies and monitoring, mentor senior scientists, and advise leadership on scientific direction.

Lead and grow an applied science team building reliable, production-ready generative AI systems for legal use. Own end-to-end AI system readiness, set technical direction, perform evaluations and error analysis, partner cross-functionally to move work to scale, hire and coach staff, and represent the team externally.

Lead development and application of analytics, statistical models, and dashboards to support R&D Quality oversight. Integrate clinical, safety, lab, and operational data to identify risks, support audit/inspection readiness, enable RBQM, and provide actionable quality insights and recommendations to cross-functional partners.

Lead strategic vision and execution of next-generation bioinformatics technologies. Identify and evaluate emerging computational methods, translate research into production-grade pipelines and prototypes, support product roadmaps and technology transfer, and partner cross-functionally to commercialize genomic and AI-driven healthcare solutions.

Develop and scale machine learning training systems for robotics data, optimize training pipelines, and collaborate with ML researchers to enhance autonomy models.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

Build and maintain scalable ML and generative AI platforms and backend infrastructure; deploy and manage production applications; create services exposing ML/AI products; implement RAG solutions and vector databases; integrate LLM orchestration and foundation model APIs; collaborate cross-functionally and mentor teammates.

Lead development of an AI-enabled Ethereum Layer 2 platform: build front-end and back-end systems, deploy and optimize AI models, create data pipelines, collaborate on model training, and contribute to product innovation and other company projects.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

Embed with clients to gather requirements and design AI-driven solutions for fraud and fincrime. Architect, train, evaluate, and deploy custom AI agents and workflows, optimize model performance, establish risk metrics and evaluation pipelines, and collaborate with engineering/product teams to scale into production.

Own Oscilar's AML product suite (transaction monitoring, KYC/KYB, screening, case management, SAR filing, AI agents). Define detection rules, model calibration, data strategy, and defensible audit trails. Collaborate with engineers and compliance, use AI across discovery/design/analysis, deliver PRDs, validate models, and ship production features.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

The AI & Data Science Director will lead AI strategies, foster technical leadership, support team development, and integrate generative AI into products.

The Senior Generative AI Engineer will design and deploy AI/ML solutions, focusing on Generative AI systems and their operational excellence across various sectors like R&D and Clinical Trials.

The Technical Product Owner will lead product initiatives by defining requirements, managing the product backlog, and ensuring successful payment integrations while collaborating with engineering and risk teams.