Top Senior Machine Learning Jobs in Birmingham, AL

The Senior Data Scientist will design and implement data-driven initiatives, optimize product offerings using AI/ML, and collaborate with engineers on scalable solutions.

The Engineering Manager will lead a team of Data Scientists and ML Engineers to build a Dispatch Optimization platform, focusing on model deployment and operational excellence.

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

As a Senior Software Engineer, you'll enhance servicing decisions with ML models, improve experimentation, and scale decisioning systems for personalized borrower experiences.

You will tackle AI challenges, develop scalable software and collaborate with teams to enhance healthcare navigation using AI solutions.

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

Lead the Machine Learning Engineering team at AKASA, focusing on improving ML capabilities, model deployment, and infrastructure development, while managing and mentoring engineers.

Design, build, and scale production ML systems (including LLMs) to automate customer support and compliance workflows. Lead technical roadmaps, write high-quality Python code, mentor engineers, ensure secure, scalable architectures, and resolve complex reliability issues.

Partner with CV researchers to productionize models, optimize training and real-time inference performance, design reusable abstractions, and collaborate with MLOps/backend teams to evolve the CV inference platform for scale and reliability.

The Talent Researcher role involves building talent maps in AI, ML, and voice technology, translating hiring signals into research plans, and delivering market intelligence to enhance recruitment processes.

The Senior Product Manager will streamline analytics workflows, manage governance, conduct user research, develop product requirements, and promote AI tools to internal users in healthcare analytics.

The Brand Marketing Manager will develop content strategies for lead generation, produce high-quality marketing assets, collaborate with the Demand Generation team, and analyze data to optimize campaigns.

Lead the Ad Ranking team, focusing on improving ad quality and performance using machine learning. Responsibilities include team management, stakeholder collaboration, and executing analytical initiatives.

The Staff Software Engineer, AI role involves defining technical direction for AI applications, mentoring engineers, and enhancing patient-provider interactions through advanced language and voice technologies.

Lead product strategy and development in cybersecurity, focusing on supply chain security solutions. Engage with customers and cross-functional teams to drive product innovation and performance metrics.

The AI Design Engineer leads AI solutions development for nuclear and energy sectors, focusing on model implementation, performance validation, and integration with existing systems.

Lead and grow the engineering team, architect the core AI platform, manage data infrastructure, and drive best practices in software development.

Lead and scale Zapier's AI/ML organization by defining strategy, delivering ML products and platforms, coaching teams, enabling product partners, and ensuring safe, reliable, cost-effective model deployment and operations.

The VP Analyst will provide insights to C-level clients on enterprise application services and AI capabilities, conduct research and analysis, and develop thought leadership content while advising clients on strategies and implementations.

As a Data Scientist, you will build predictive models, develop software tools, and analyze geoscientific data to support mineral exploration and discovery.